ORCID Profile
0000-0002-8515-6324
Current Organisation
Queensland University of Technology
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Computer Vision | Artificial Intelligence and Image Processing | Pattern Recognition and Data Mining | Image Processing | Simulation and Modelling | Signal Processing | Ore Deposit Petrology | Design Innovation | Simulation And Modelling | Geochemistry | Statistics | Infrastructure Engineering and Asset Management | Civil Engineering | Exploration Geochemistry | Decision Support and Group Support Systems | Knowledge Representation and Machine Learning | Geochronology | Calculus of Variations, Systems Theory and Control Theory | Applied Statistics | Interdisciplinary Engineering Not Elsewhere Classified | Interdisciplinary Engineering | Biomechanics | Computer Vision
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in the Information and Computing Sciences | National Security | Information and Communication Services not elsewhere classified | Air Terminal Infrastructure and Management | Management and productivity issues not elsewhere classified | Computer Software and Services not elsewhere classified | Intelligence | Integrated systems | Air transport | Expanding Knowledge in Technology | Application Software Packages (excl. Computer Games) | Evaluation of Health Outcomes | Copper Ore Exploration | Expanding Knowledge in the Mathematical Sciences |
Related Links
Publications
From Affine Rank Minimization Solution to Sparse Modeling
Publisher: IEEE
Date: 03-2017
DOI: 10.1109/WACV.2017.62
Eigengaze - Covert behavioral biometric exploiting visual attention characteristics
Publisher: IEEE
Date: 05-2010
Searching for people using semantic soft biometric descriptions
Publisher: Elsevier BV
Date: 12-2015
Continuous Human Action Recognition for Human-machine Interaction: A Review
Publisher: Association for Computing Machinery (ACM)
Date: 13-07-2023
DOI: 10.1145/3587931
Abstract: With advances in data-driven machine learning research, a wide variety of prediction models have been proposed to capture spatio-temporal features for the analysis of video streams. Recognising actions and detecting action transitions within an input video are challenging but necessary tasks for applications that require real-time human-machine interaction. By reviewing a large body of recent related work in the literature, we thoroughly analyse, explain, and compare action segmentation methods and provide details on the feature extraction and learning strategies that are used on most state-of-the-art methods. We cover the impact of the performance of object detection and tracking techniques on human action segmentation methodologies. We investigate the application of such models to real-world scenarios and discuss several limitations and key research directions towards improving interpretability, generalisation, optimisation, and deployment.
Generalized Generative Deep Learning Models for Biosignal Synthesis and Modality Transfer
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Determining operational measures from multi-camera surveillance systems using soft biometrics
Publisher: IEEE
Date: 08-2011
An evaluation of different features and learning models for anomalous event detection
Publisher: IEEE
Date: 11-2013
Accurate silhouette segmentation using motion detection and graph cuts
Publisher: IEEE
Date: 05-2010
Semi-binary based video features for activity representation
Publisher: IEEE
Date: 11-2013
Attentional perceptual thresholds for manipulated digitized mammograms
Publisher: SPIE
Date: 04-05-2004
DOI: 10.1117/12.536984
Agent-Based Modelling Simulation Case Study: Assessment of Airport Check-In and Evacuation Process by Considering Group Travel Behaviour of Air Passengers
Publisher: Trans Tech Publications, Ltd.
Date: 06-2014
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMM.568-570.1859
Abstract: Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.
A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Learning test-time augmentation for content-based image retrieval
Publisher: Elsevier BV
Date: 09-2022
Automatic Solder Joint Defect Classification using the Log-Gabor Filter
Publisher: Trans Tech Publications, Ltd.
Date: 03-2010
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMR.97-101.2940
Abstract: This paper proposes the validity of a Gabor filter bank for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance measure based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.
Gait energy volumes and frontal gait recognition using depth images
Publisher: IEEE
Date: 10-2011
Speakers in the wild (SITW): The QUT speaker recognition system
Publisher: ISCA
Date: 08-09-2016
Complex Event Detection Using Joint Max Margin and Semantic Features
Publisher: IEEE
Date: 11-2016
Evaluating automatic road detection across a large aerial imagery collection
Publisher: IEEE
Date: 12-2011
Tree Memory Networks for modelling long-term temporal dependencies
Publisher: Elsevier BV
Date: 08-2018
Scene Invariant Virtual Gates Using DNNs
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Accurate silhouettes for surveillance - Improved motion segmentation using graph cuts
Publisher: IEEE
Date: 12-2010
3D face verification using a free-parts approach
Publisher: Elsevier BV
Date: 07-2008
Non-Invasive Performance Measurement in Combat Sports
Publisher: Springer International Publishing
Date: 03-11-2016
Component-Based Attention for Large-Scale Trademark Retrieval
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Multi-stage stacked temporal convolution neural networks (MS-S-TCNs) for biosignal segmentation and anomaly localization
Publisher: Elsevier BV
Date: 07-2023
Rigid medical image registration and its association with mutual information
Publisher: World Scientific Pub Co Pte Lt
Date: 11-2003
DOI: 10.1142/S0218001403002800
Abstract: Image registration plays a crucial role in the computer vision and medical imaging field where it is used to develop a spatial mapping between different sets of data. These transformations can range from simple rigid registrations to complex nonrigid deformations. Mutual information (MI) is a popular entropy-based similarity measure which has recently experienced a prolific expansion in a number of image registration applications. Stemming from information theory, this measure generally outperforms most other intensity-based measures in multimodal applications as it only assumes a statistical dependence between images. This paper provides a thorough introduction to the MI measure and its use in rigid medical image registration. A look at the extensions proposed to the original measure will also be provided. These were developed to improve the robustness of the measure and to avoid certain cases when maximizing MI does not lead to the correct spatial alignment.
Resection-Intersection Bundle Adjustment Revisited
Publisher: Hindawi Limited
Date: 12-12-2013
DOI: 10.1155/2013/261956
Abstract: Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.
Automatic surveillance in transportation hubs: No longer just about catching the bad guy
Publisher: Elsevier BV
Date: 12-2015
An MRF based abnormal event detection approach using motion and appearance features
Publisher: IEEE
Date: 08-2014
Design and development of automatic visual inspection system for PCB manufacturing
Publisher: Elsevier BV
Date: 10-2011
Quality Based Frame Selection for Face Clustering in News Video
Publisher: IEEE
Date: 11-2013
Spatiotemporal Camera-LiDAR Calibration: A Targetless and Structureless Approach
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Impact of Passenger Group Dynamics on an Airport Evacuation Process Using an Agent-Based Model
Publisher: IEEE
Date: 03-2014
Going Deeper: Autonomous Steering with Neural Memory Networks
Publisher: IEEE
Date: 10-2017
Tracking by Prediction: A Deep Generative Model for Mutli-person Localisation and Tracking
Publisher: IEEE
Date: 03-2018
Super-resolution for biometrics: A comprehensive survey
Publisher: Elsevier BV
Date: 06-2018
Scene invariant crowd counting and crowd occupancy analysis
Publisher: Springer Berlin Heidelberg
Date: 2012
Identifying Customer Behaviour and Dwell Time Using Soft Biometrics
Publisher: Springer Berlin Heidelberg
Date: 2012
Short utterance variance modelling and utterance partitioning for PLDA speaker verification
Publisher: ISCA
Date: 08-09-2016
An Exploration of Feature Detector Performance in the Thermal-Infrared Modality
Publisher: IEEE
Date: 12-2011
Understanding Patients’ Behavior: Vision-Based Analysis of Seizure Disorders
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2019
First-episode psychosis is characterized by failure of deactivation but not by hypo- or hyperfrontality
Publisher: Cambridge University Press (CUP)
Date: 07-07-2011
DOI: 10.1017/S0033291711001073
Abstract: It is not known whether first-episode psychosis is characterized by the same prefrontal cortex functional imaging abnormalities as chronic schizophrenia. Thirty patients with a first episode of non-affective functional psychosis and 28 healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back working memory task. Voxel-based analyses of brain activations and deactivations were carried out and compared between groups. The connectivity of regions of significant difference between the patients and controls was also examined. The first-episode patients did not show significant prefrontal hypo- or hyperactivation compared to controls. However, they showed failure of deactivation in the medial frontal cortex. This area showed high levels of connectivity with the posterior cingulate gyrus recuneus and parts of the parietal cortex bilaterally. Failure of deactivation was significantly greater in first-episode patients who had or went on to acquire a DSM-IV diagnosis of schizophrenia than in those who did not, and in those who met RDC criteria for schizophrenia compared to those who did not. First-episode psychosis is not characterized by hypo- or hyperfrontality but instead by a failure of deactivation in the medial frontal cortex. The location and connectivity of this area suggest that it is part of the default mode network. The failure of deactivation seems to be particularly marked in first-episode patients who have, or progress to, schizophrenia.
Quality-Driven Super-Resolution for Less Constrained Iris Recognition at a Distance and on the Move
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2011
Detection of Fake and Fraudulent Faces via Neural Memory Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Heart Sound Segmentation Using Bidirectional LSTMs With Attention
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Real-time video event detection in crowded scenes using MPEG derived features : a multiple instance learning approach
Publisher: Elsevier BV
Date: 07-2014
Vertical Axis Detection for Sport Video Analytics
Publisher: IEEE
Date: 11-2016
Score-Level Multibiometric Fusion Based on Dempster–Shafer Theory Incorporating Uncertainty Factors
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2015
Detecting rare events using Kullback-Leibler divergence
Publisher: IEEE
Date: 04-2015
Feature-domain super-resolution for iris recognition
Publisher: Elsevier BV
Date: 10-2013
Dynamic performance measures for object tracking systems
Publisher: IEEE
Date: 09-2009
DOI: 10.1109/AVSS.2009.32
Gaze Based Personal Identification
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-60566-725-6.CH012
Abstract: This chapter describes the use of visual attention characteristics as a biometric for authentication or identification of in idual viewers. The visual attention characteristics of a person can be easily monitored by tracking the gaze of a viewer during the presentation of a known or unknown visual scene. The positions and sequences of gaze locations during viewing may be determined by overt (conscious) or covert (subconscious) viewing behaviour. Methods to quantify the spatial and temporal patterns established by the viewer for both overt and covert behaviours are proposed. The former behaviour entails a simple PIN-like approach to develop an independent signature while the latter behaviour is captured through three proposed techniques: a principal component analysis technique (‘eigenGaze’) a linear discriminant analysis technique and a fusion of distance measures. Experimental results suggest that both types of gaze behaviours can provide simple and effective biometrics for this application.
Large scale monitoring of crowds and building utilisation: A new database and distributed approach
Publisher: IEEE
Date: 08-2015
Deep Learning for Patient-Independent Epileptic Seizure Prediction Using Scalp EEG Signals
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Closed-Form Solutions for Low-Rank Non-Rigid Reconstruction
Publisher: IEEE
Date: 11-2016
Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Face recognition from 3D data using iterative closest point algorithm and gaussian mixture models
Publisher: IEEE
Date: 2004
Toward On-Board Panoptic Segmentation of Multispectral Satellite Images
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Segmentation-based image compression using BTC-VQ technique
Publisher: IEEE
Date: 2003
Neural memory plasticity for medical anomaly detection
Publisher: Elsevier BV
Date: 07-2020
Detecting rare events using Kullback–Leibler divergence: A weakly supervised approach
Publisher: Elsevier BV
Date: 07-2016
Liveness detection based on 3D face shape analysis
Publisher: IEEE
Date: 04-2013
Fine-grained action recognition of boxing punches from depth imagery
Publisher: Elsevier BV
Date: 06-2017
Discovering Team Structures in Soccer from Spatiotemporal Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2016
Check-in processing : simulation of passengers with advanced traits
Publisher: IEEE
Date: 12-2011
Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2023
DConv-LSTM-Net: A Novel Architecture for Single- and 12-Lead ECG Anomaly Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Feature-domain super-resolution framework for Gabor-based face and iris recognition
Publisher: IEEE
Date: 06-2012
Robust Photogeometric Localization Over Time for Map-Centric Loop Closure
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Multi-modal object tracking using dynamic performance metrics
Publisher: IEEE
Date: 08-2010
DOI: 10.1109/AVSS.2010.16
Improved grabcut segmentation via GMM optimisation
Publisher: IEEE
Date: 2008
Labelled silhouettes for human pose estimation
Publisher: IEEE
Date: 05-2010
Soft-Biometrics: Unconstrained Authentication in a Surveillance Environment
Publisher: IEEE
Date: 2009
A multi-class tracker using a scalable condensation filter
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.7
Fruit Quantity and Ripeness Estimation Using a Robotic Vision System
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2018
Constrained Design of Deep Iris Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Improved simultaneous computation of motion detection and optical flow for object tracking
Publisher: IEEE
Date: 2009
Use of brain computer interface to drive
Publisher: ACM
Date: 17-10-2012
Normalisation and Recognition of 3D Face Data Using Robust Hausdorff Metric
Publisher: IEEE
Date: 2008
An Efficient and Robust System for Multiperson Event Detection in Real-World Indoor Surveillance Scenes
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Class-specific sparse codes for representing activities
Publisher: IEEE
Date: 09-2015
Physical Adversarial Attacks for Surveillance: A Survey
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling
Publisher: IEEE
Date: 09-2016
Recent advances in camera planning for large area surveillance: A comprehensive review
Publisher: Association for Computing Machinery (ACM)
Date: 23-05-2016
DOI: 10.1145/2906148
Abstract: With recent advances in consumer electronics and the increasingly urgent need for public security, camera networks have evolved from their early role of providing simple and static monitoring to current complex systems capable of obtaining extensive video information for intelligent processing, such as target localization, identification, and tracking. In all cases, it is of vital importance that the optimal camera configuration (i.e., optimal location, orientation, etc.) is determined before cameras are deployed as a suboptimal placement solution will adversely affect intelligent video surveillance and video analytic algorithms. The optimal configuration may also provide substantial savings on the total number of cameras required to achieve the same level of utility. In this article, we examine most, if not all, of the recent approaches (post 2000) addressing camera placement in a structured manner. We believe that our work can serve as a first point of entry for readers wishing to start researching into this area or engineers who need to design a camera system in practice. To this end, we attempt to provide a complete study of relevant formulation strategies and brief introductions to most commonly used optimization techniques by researchers in this field. We hope our work to be inspirational to spark new ideas in the field.
Optimal grid point selection for improved non-rigid medical image registration
Publisher: SPIE
Date: 12-05-2004
DOI: 10.1117/12.536828
Jointly Trained Conversion Model With LPCNet for Any-to-One Voice Conversion Using Speaker-Independent Linguistic Features
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Fusing shrinking and expanding active contour models for robust iris segementation
Publisher: IEEE
Date: 05-2010
Social signal processing for pain monitoring using a hidden conditional random field
Publisher: IEEE
Date: 06-2014
Human face reconstruction using Bayesian deformable models
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.60
Feature-domain super-resolution for iris recognition
Publisher: No publisher found
Date: 2011
Activity analysis in complicated scenes using DFT coefficients of particle trajectories
Publisher: IEEE
Date: 09-2012
DOI: 10.1109/AVSS.2012.6
Lip detection for audio-visual speech recognition in-car environment
Publisher: IEEE
Date: 05-2010
Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Local inter-session variability modelling for object classification
Publisher: IEEE
Date: 03-2014
Complex-Valued Iris Recognition Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Temporarily-Aware Context Modeling Using Generative Adversarial Networks for Speech Activity Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Crowd counting using multiple local features
Publisher: IEEE
Date: 2009
A flexible hierarchical approach for facial age estimation based on multiple features
Publisher: Elsevier BV
Date: 06-2015
Iris Recognition With Off-the-Shelf CNN Features: A Deep Learning Perspective
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Discovery of facial motions using deep machine perception
Publisher: IEEE
Date: 03-2016
Group segmentation during object tracking using optical flow discontinuities
Publisher: IEEE
Date: 11-2010
PhD forum: Multiple camera management using wide base-line matching
Publisher: IEEE
Date: 08-2009
Robust Automatic Face Clustering in News Video
Publisher: IEEE
Date: 11-2016
Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Agent-Based Application on Different Boarding Strategies
Publisher: Trans Tech Publications, Ltd.
Date: 06-2014
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMM.568-570.1893
Abstract: In this paper we implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to minimize boarding time and turnaround time for Boeing 777 and Airbus 380 aircrafts by using Agent-based modelling approach. In the simulation, we ided passengers into six different categories which are group size more than 5 people, passengers with child, gold members, first class passengers, business class passengers and economy class passengers. Results from the simulation demonstrates Reverse Pyramid method is the best boarding method for Boeing 777 and Steffen method is the best boarding method for Airbus 380.
Automated analysis of seizure semiology and brain electrical activity in presurgery evaluation of epilepsy: A focused survey
Publisher: Wiley
Date: 09-10-2017
DOI: 10.1111/EPI.13907
Abstract: Epilepsy being one of the most prevalent neurological disorders, affecting approximately 50 million people worldwide, and with almost 30-40% of patients experiencing partial epilepsy being nonresponsive to medication, epilepsy surgery is widely accepted as an effective therapeutic option. Presurgical evaluation has advanced significantly using noninvasive techniques based on video monitoring, neuroimaging, and electrophysiological and neuropsychological tests however, certain clinical settings call for invasive intracranial recordings such as stereoelectroencephalography (SEEG), aiming to accurately map the eloquent brain networks involved during a seizure. Most of the current presurgical evaluation procedures focus on semiautomatic techniques, where surgery diagnosis relies immensely on neurologists' experience and their time-consuming subjective interpretation of semiology or the manifestations of epilepsy and their correlation with the brain's electrical activity. Because surgery misdiagnosis reaches a rate of 30%, and more than one-third of all epilepsies are poorly understood, there is an evident keen interest in improving diagnostic precision using computer-based methodologies that in the past few years have shown near-human performance. Among them, deep learning has excelled in many biological and medical applications, but has advanced insufficiently in epilepsy evaluation and automated understanding of neural bases of semiology. In this paper, we systematically review the automatic applications in epilepsy for human motion analysis, brain electrical activity, and the anatomoelectroclinical correlation to attribute anatomical localization of the epileptogenic network to distinctive epilepsy patterns. Notably, recent advances in deep learning techniques will be investigated in the contexts of epilepsy to address the challenges exhibited by traditional machine learning techniques. Finally, we discuss and propose future research on epilepsy surgery assessment that can jointly learn across visually observed semiologic patterns and recorded brain electrical activity.
Multi-spectral fusion for surveillance systems
Publisher: Elsevier BV
Date: 07-2010
Two Stream LSTM : A Deep Fusion Framework for Human Action Recognition
Publisher: IEEE
Date: 03-2017
DOI: 10.1109/WACV.2017.27
A Mask-Based Approach for the Geometric Calibration of Thermal-Infrared Cameras
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2012
Searching for semantic person queries using channel representations
Publisher: IEEE
Date: 04-2015
A hierarchical multimodal system for motion analysis in patients with epilepsy
Publisher: Elsevier BV
Date: 10-2018
Elasticity Meets Continuous-Time:Map-Centric Dense 3D LiDAR SLAM
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Improving deep convolutional neural networks with unsupervised feature learning
Publisher: IEEE
Date: 09-2015
Textures of optical flow for real-time anomaly detection in crowds
Publisher: No publisher found
Date: 2011
Dense correspondence extraction in difficult uncalibrated scenarios
Publisher: IEEE
Date: 2009
Hessian-based affine adaptation of salient local image features
Publisher: Springer Science and Business Media LLC
Date: 28-09-2012
Human-level face verification with intra-personal factor analysis and deep face representation
Publisher: Institution of Engineering and Technology (IET)
Date: 12-03-2018
Robust and Interpretable Temporal Convolution Network for Event Detection in Lung Sound Recordings
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Focus-score weighted super-resolution for uncooperative iris recognition at a distance and on the move
Publisher: IEEE
Date: 11-2010
Learning Temporal Alignment Uncertainty for Efficient Event Detection
Publisher: IEEE
Date: 11-2016
Affine adaptation of local image features using the Hessian matrix
Publisher: IEEE
Date: 09-2009
DOI: 10.1109/AVSS.2009.8
Compressive sensing for gait recognition
Publisher: IEEE
Date: 12-2011
Investigation & comparison of robust stereo image matching using mutual information & hierarchical prior probabilities
Publisher: IEEE
Date: 12-2008
3-D Bi-directional LSTM for Satellite Soil Moisture Downscaling
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
An evaluation of crowd counting methods, features and regression models
Publisher: Elsevier BV
Date: 2015
Detecting anomalous events at railway level crossings
Publisher: SAGE Publications
Date: 09-2013
Abstract: Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of in iduals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.
Wide baseline correspondence extraction beyond local features
Publisher: Institution of Engineering and Technology (IET)
Date: 2011
Efficient real-time face detection for high resolution surveillance applications
Publisher: IEEE
Date: 12-2012
Quality based frame selection for video face recognition
Publisher: IEEE
Date: 12-2012
Evaluation of image resolution and super-resolution on face recognition performance
Publisher: Elsevier BV
Date: 2012
Multi-spectral stereo image matching using mutual information
Publisher: IEEE
Date: 2004
Dynamic Texture reconstruction from sparse codes for unusual event detection in crowded scenes
Publisher: ACM
Date: 30-11-2011
Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks
Publisher: IEEE
Date: 03-2018
Scene invariant crowd counting for real-time surveillance
Publisher: IEEE
Date: 12-2008
Multi-modal deformable medical image registration
Publisher: IEEE
Date: 12-2008
Acoustic adaptation in cross database audio visual SHMM training for phonetic spoken term detection
Publisher: ACM Press
Date: 2015
Object tracking using multiple motion modalities
Publisher: IEEE
Date: 12-2008
Deep Context Modeling for Semantic Segmentation
Publisher: IEEE
Date: 03-2017
DOI: 10.1109/WACV.2017.14
Using Synthetic Data to Improve Facial Expression Analysis with 3D Convolutional Networks
Publisher: IEEE
Date: 10-2017
Crowd counting using group tracking and local features
Publisher: IEEE
Date: 08-2010
DOI: 10.1109/AVSS.2010.30
3D ellipsoid fitting for multi-view gait recognition
Publisher: IEEE
Date: 08-2011
A framework for model integration and holistic modelling of socio-technical systems
Publisher: Elsevier BV
Date: 03-2015
The role of motion models in super-resolving surveillance video for face recognition
Publisher: IEEE
Date: 11-2006
Rethinking Planar Homography Estimation Using Perspective Fields
Publisher: Springer International Publishing
Date: 2019
Optimal camera planning under versatile user constraints in multi-camera image processing systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2014
Automatic UAV Forced Landing Site Detection Using Machine Learning
Publisher: IEEE
Date: 11-2014
Supervised latent dirichlet allocation models for efficient activity representation
Publisher: IEEE
Date: 11-2015
Evaluation of two-view geometry methods with automatic ground-truth generation
Publisher: Elsevier BV
Date: 12-2013
SESS: Saliency Enhancing with Scaling and Sliding
Publisher: Springer Nature Switzerland
Date: 2022
Interpretable Seizure Classification Using Unprocessed EEG With Multi-Channel Attentive Feature Fusion
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2021
A study on the effects of using short utterance length development data in the design of GPLDA speaker verification systems
Publisher: Springer Science and Business Media LLC
Date: 16-02-2017
Deformable face ensemble alignment with robust grouped-L1 anchors
Publisher: IEEE
Date: 04-2013
Anomalous event detection using a semi-two dimensional hidden Markov model
Publisher: IEEE
Date: 12-2012
Deep facial analysis: A new phase I epilepsy evaluation using computer vision
Publisher: Elsevier BV
Date: 05-2018
DOI: 10.1016/J.YEBEH.2018.02.010
Abstract: Semiology observation and characterization play a major role in the presurgical evaluation of epilepsy. However, the interpretation of patient movements has subjective and intrinsic challenges. In this paper, we develop approaches to attempt to automatically extract and classify semiological patterns from facial expressions. We address limitations of existing computer-based analytical approaches of epilepsy monitoring, where facial movements have largely been ignored. This is an area that has seen limited advances in the literature. Inspired by recent advances in deep learning, we propose two deep learning models, landmark-based and region-based, to quantitatively identify changes in facial semiology in patients with mesial temporal lobe epilepsy (MTLE) from spontaneous expressions during phase I monitoring. A dataset has been collected from the Mater Advanced Epilepsy Unit (Brisbane, Australia) and is used to evaluate our proposed approach. Our experiments show that a landmark-based approach achieves promising results in analyzing facial semiology, where movements can be effectively marked and tracked when there is a frontal face on visualization. However, the region-based counterpart with spatiotemporal features achieves more accurate results when confronted with extreme head positions. A multifold cross-validation of the region-based approach exhibited an average test accuracy of 95.19% and an average AUC of 0.98 of the ROC curve. Conversely, a leave-one-subject-out cross-validation scheme for the same approach reveals a reduction in accuracy for the model as it is affected by data limitations and achieves an average test accuracy of 50.85%. Overall, the proposed deep learning models have shown promise in quantifying ictal facial movements in patients with MTLE. In turn, this may serve to enhance the automated presurgical epilepsy evaluation by allowing for standardization, mitigating bias, and assessing key features. The computer-aided diagnosis may help to support clinical decision-making and prevent erroneous localization and surgery.
Negative determinant of hessian features
Publisher: IEEE
Date: 12-2011
Deep Spatio-Temporal Features for Multimodal Emotion Recognition
Publisher: IEEE
Date: 03-2017
Unusual scene detection using distributed behaviour model and sparse representation
Publisher: IEEE
Date: 09-2012
DOI: 10.1109/AVSS.2012.80
Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion
Publisher: IEEE
Date: 12-2011
Activity recognition using binary tree SVM
Publisher: IEEE
Date: 06-2014
Channel Graph Regularized Correlation Filters for Visual Object Tracking
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Unusual event detection in crowded scenes using bag of LBPs in spatio-temporal patches
Publisher: IEEE
Date: 12-2011
Histogram of weighted local directions for gait recognition
Publisher: IEEE
Date: 06-2013
Scene invariant multi camera crowd counting
Publisher: Elsevier BV
Date: 07-2014
Multi-view intelligent vehicle surveillance system
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.78
Can You Describe Him for Me? A Technique for Semantic Person Search in Video
Publisher: IEEE
Date: 12-2012
A Deep Four-Stream Siamese Convolutional Neural Network with Joint Verification and Identification Loss for Person Re-Detection
Publisher: IEEE
Date: 03-2018
Gabor filter bank representation for 3D face recognition
Publisher: IEEE
Date: 2005
Domain Generalization in Biosignal Classification
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Spatio temporal feature evaluation for action recognition
Publisher: IEEE
Date: 12-2012
Processing passengers efficiently: An analysis of airport processing times for international passengers
Publisher: Elsevier BV
Date: 10-2015
A Database for Person Re-Identification in Multi-Camera Surveillance Networks
Publisher: IEEE
Date: 12-2012
Locating People in Video from Semantic Descriptions: A New Database and Approach
Publisher: IEEE
Date: 08-2014
Plasma levels of soluble CD14 independently predict mortality in HIV infection
Publisher: Oxford University Press (OUP)
Date: 15-03-2011
Multiple instance dictionary learning for activity representation
Publisher: IEEE
Date: 08-2014
Semi-supervised intelligent surveillance system for secure environments
Publisher: IEEE
Date: 07-2010
Deep Auto-Encoders With Sequential Learning for Multimodal Dimensional Emotion Recognition
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move
Publisher: ACM Press
Date: 2010
The backfilled GEI - A cross-capture modality gait feature for frontal and side-view gait recognition
Publisher: IEEE
Date: 12-2012
Improved subject identification in surveillance video using super-resolution
Publisher: IGI Global
Date: 2012
DOI: 10.4018/978-1-4666-2660-7.CH011
Abstract: The time consuming and labour intensive task of identifying in iduals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be tracked. A number of instances of such regions can then be utilized to obtain a super-resolved version for matching. Performance improvement from super-resolution is demonstrated using a face verification task. It is shown that there is a consistent improvement of approximately 7% in verification accuracy, using both Eigenface and Elastic Bunch Graph Matching approaches for automatic face verification, starting from faces with an eye to eye distance of 14 pixels. Visual improvement in image fidelity from super-resolved images over low-resolution and interpolated images is demonstrated on a small database. Current research and future directions in this area are also summarized.
TMMF: Temporal Multi-Modal Fusion for Single-Stage Continuous Gesture Recognition
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
On the statistical determination of optimal camera configurations in large scale surveillance networks
Publisher: Springer Berlin Heidelberg
Date: 2012
Activity modelling in crowded environments: A soft-decision approach
Publisher: IEEE
Date: 12-2011
Long range iris recognition: A survey
Publisher: Elsevier BV
Date: 12-2017
Probabilistic Surfel Fusion for Dense LiDAR Mapping
Publisher: IEEE
Date: 10-2017
Visual voice activity detection using frontal versus profile views
Publisher: IEEE
Date: 12-2011
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