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David C. Hogg
David Crossland Hogg – David Hogg 0001
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- affiliation: University of Leeds, School of Computing, UK
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2020 – today
- 2024
- [j35]Yunfeng Diao, He Wang, Tianjia Shao, Yongliang Yang, Kun Zhou, David C. Hogg, Meng Wang:
Understanding the vulnerability of skeleton-based Human Activity Recognition via black-box attack. Pattern Recognit. 153: 110564 (2024) - [c98]Fangjun Li, David C. Hogg, Anthony G. Cohn:
Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark. AAAI 2024: 18500-18507 - [c97]Fangjun Li, David C. Hogg, Anthony G. Cohn:
Reframing Spatial Reasoning Evaluation in Language Models: A Real-World Simulation Benchmark for Qualitative Reasoning. IJCAI 2024: 6342-6349 - [i19]Fangjun Li, David C. Hogg, Anthony G. Cohn:
Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark. CoRR abs/2401.03991 (2024) - [i18]Fangjun Li, David C. Hogg, Anthony G. Cohn:
Reframing Spatial Reasoning Evaluation in Language Models: A Real-World Simulation Benchmark for Qualitative Reasoning. CoRR abs/2405.15064 (2024) - 2023
- [c96]Rebecca S. Stone, Pedro Esteban Chavarrias-Solano, Andrew J. Bulpitt, David C. Hogg, Sharib Ali:
Bayesian Uncertainty-Weighted Loss for Improved Generalisability on Polyp Segmentation Task. CLIP/FAIMI/EPIMI@MICCAI 2023: 153-162 - [c95]Jose Sosa, David C. Hogg:
Self-supervised 3D Human Pose Estimation from a Single Image. CVPR Workshops 2023: 4788-4797 - [c94]Thomas P. Ilett, Omer Yuval, Thomas Ranner, Netta Cohen, David C. Hogg:
3D Shape Reconstruction of Semi-Transparent Worms. CVPR 2023: 12565-12575 - [c93]Jose Sosa, David C. Hogg:
A Horse with no Labels: Self-Supervised Horse Pose Estimation from Unlabelled Images and Synthetic Prior. ICCV (Workshops) 2023: 1041-1048 - [c92]Jose Sosa, Sharn Perry, Jane E. Alty, David C. Hogg:
Of Mice and Pose: 2D Mouse Pose Estimation from Unlabelled Data and Synthetic Prior. ICVS 2023: 125-136 - [i17]Jose Sosa, David Hogg:
Self-supervised 3D Human Pose Estimation from a Single Image. CoRR abs/2304.02349 (2023) - [i16]Thomas P. Ilett, Omer Yuval, Thomas Ranner, Netta Cohen, David C. Hogg:
3D shape reconstruction of semi-transparent worms. CoRR abs/2304.14841 (2023) - [i15]Jose Sosa, Sharn Perry, Jane E. Alty, David C. Hogg:
Of Mice and Pose: 2D Mouse Pose Estimation from Unlabelled Data and Synthetic Prior. CoRR abs/2307.13361 (2023) - [i14]Jose Sosa, David C. Hogg:
A Horse with no Labels: Self-Supervised Horse Pose Estimation from Unlabelled Images and Synthetic Prior. CoRR abs/2308.03411 (2023) - [i13]Rebecca S. Stone, Pedro Esteban Chavarrias-Solano, Andrew J. Bulpitt, David C. Hogg, Sharib Ali:
Bayesian uncertainty-weighted loss for improved generalisability on polyp segmentation task. CoRR abs/2309.06807 (2023) - 2022
- [j34]Muhannad Al-Omari, Fangjun Li, David C. Hogg, Anthony G. Cohn:
Online perceptual learning and natural language acquisition for autonomous robots. Artif. Intell. 303: 103637 (2022) - [j33]Renjie Li, Rebecca J. St George, Xinyi Wang, Katherine Lawler, Edward Hill, Saurabh Garg, Stefan Williams, Samuel D. Relton, David Hogg, Quan Bai, Jane E. Alty:
Moving towards intelligent telemedicine: Computer vision measurement of human movement. Comput. Biol. Medicine 147: 105776 (2022) - [c91]Rebecca S. Stone, Nishant Ravikumar, Andrew J. Bulpitt, David C. Hogg:
Epistemic Uncertainty-Weighted Loss for Visual Bias Mitigation. CVPR Workshops 2022: 2897-2904 - [c90]Simin Hong, Anthony G. Cohn, David Crossland Hogg:
Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms. ICLR 2022 - [c89]Mohammed M. Alghamdi, He Wang, Andrew J. Bulpitt, David C. Hogg:
Talking Head from Speech Audio using a Pre-trained Image Generator. ACM Multimedia 2022: 5228-5236 - [i12]Rebecca S. Stone, Nishant Ravikumar, Andrew J. Bulpitt, David C. Hogg:
Epistemic Uncertainty-Weighted Loss for Visual Bias Mitigation. CoRR abs/2204.09389 (2022) - [i11]Hanh Thi Minh Tran, David Hogg:
Anomaly detection using prediction error with Spatio-Temporal Convolutional LSTM. CoRR abs/2205.08812 (2022) - [i10]Fangjun Li, David C. Hogg, Anthony G. Cohn:
Exploring the GLIDE model for Human Action-effect Prediction. CoRR abs/2208.01136 (2022) - [i9]Mohammed M. Alghamdi, He Wang, Andrew J. Bulpitt, David C. Hogg:
Talking Head from Speech Audio using a Pre-trained Image Generator. CoRR abs/2209.04252 (2022) - [i8]Yunfeng Diao, He Wang, Tianjia Shao, Yong-Liang Yang, Kun Zhou, David Hogg:
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack. CoRR abs/2211.11312 (2022) - 2021
- [j32]Leo Pauly, Wisdom C. Agboh, David C. Hogg, Raul Fuentes:
O2A: One-Shot Observational Learning with Action Vectors. Frontiers Robotics AI 8: 686368 (2021) - [c88]He Wang, Feixiang He, Zhexi Peng, Tianjia Shao, Yong-Liang Yang, Kun Zhou, David Hogg:
Understanding the Robustness of Skeleton-Based Action Recognition Under Adversarial Attack. CVPR 2021: 14656-14665 - [c87]Angelina Prima Kurniati, Eric Rojas, Kieran Zucker, Geoff Hall, David C. Hogg, Owen A. Johnson:
Process Mining to Explore Variations in Endometrial Cancer Pathways from GP Referral to First Treatment. MIE 2021: 769-773 - [i7]He Wang, Feixiang He, Zhexi Peng, Tianjia Shao, Yong-Liang Yang, Kun Zhou, David Hogg:
Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack. CoRR abs/2103.05347 (2021) - 2020
- [c86]Angelina Prima Kurniati, Geoff Hall, David C. Hogg, Owen A. Johnson:
Process Mining on the Extended Event Log to Analyse the System Usage During Healthcare Processes (Case Study: The GP Tab Usage During Chemotherapy Treatments). ICPM Workshops 2020: 330-342
2010 – 2019
- 2019
- [j31]Alison McKay, Hau Hing Chau, Christopher F. Earl, Amar Kumar Behera, Alan de Pennington, David C. Hogg:
A lattice-based approach for navigating design configuration spaces. Adv. Eng. Informatics 42 (2019) - [j30]Paul Duckworth, David C. Hogg, Anthony G. Cohn:
Unsupervised human activity analysis for intelligent mobile robots. Artif. Intell. 270: 67-92 (2019) - [j29]Angelina Prima Kurniati, Eric Rojas, David C. Hogg, Geoff Hall, Owen A. Johnson:
The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database. Health Informatics J. 25(4) (2019) - [c85]Angelina Prima Kurniati, Ciarán McInerney, Kieran Zucker, Geoff Hall, David C. Hogg, Owen A. Johnson:
A Multi-level Approach for Identifying Process Change in Cancer Pathways. Business Process Management Workshops 2019: 595-607 - [i6]He Wang, Feixiang He, Zhexi Peng, Yongliang Yang, Tianjia Shao, Kun Zhou, David Hogg:
SMART: Skeletal Motion Action Recognition aTtack. CoRR abs/1911.07107 (2019) - 2018
- [c84]Jawad Tayyub, Majd Hawasly, David C. Hogg, Anthony G. Cohn:
Learning Hierarchical Models of Complex Daily Activities from Annotated Videos. WACV 2018: 1633-1641 - [i5]Leo Pauly, Wisdom C. Agboh, Mohamed Abdellatif, David C. Hogg, Raul Fuentes:
One-Shot Observation Learning. CoRR abs/1810.07483 (2018) - 2017
- [j28]Nick Hawes, Christopher Burbridge, Ferdian Jovan, Lars Kunze, Bruno Lacerda, Lenka Mudrová, Jay Young, Jeremy L. Wyatt, Denise Hebesberger, Tobias Körtner, Rares Ambrus, Nils Bore, John Folkesson, Patric Jensfelt, Lucas Beyer, Alexander Hermans, Bastian Leibe, Aitor Aldoma, Thomas Faulhammer, Michael Zillich, Markus Vincze, Eris Chinellato, Muhannad Al-Omari, Paul Duckworth, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn, Christian Dondrup, Jaime Pulido Fentanes, Tomás Krajník, João Machado Santos, Tom Duckett, Marc Hanheide:
The STRANDS Project: Long-Term Autonomy in Everyday Environments. IEEE Robotics Autom. Mag. 24(3): 146-156 (2017) - [c83]Paul Duckworth, Muhannad Al-Omari, James Charles, David C. Hogg, Anthony G. Cohn:
Latent Dirichlet Allocation for Unsupervised Activity Analysis on an Autonomous Mobile Robot. AAAI 2017: 3819-3826 - [c82]Muhannad Al-Omari, Paul Duckworth, David C. Hogg, Anthony G. Cohn:
Natural Language Acquisition and Grounding for Embodied Robotic Systems. AAAI 2017: 4349-4356 - [c81]Muhannad Al-Omari, Paul Duckworth, David C. Hogg, Anthony G. Cohn:
Learning of Object Properties, Spatial Relations, and Actions for Embodied Agents from Language and Vision. AAAI Spring Symposia 2017 - [c80]Muhannad Al-Omari, Paul Duckworth, Majd Hawasly, David C. Hogg, Anthony G. Cohn:
Natural Language Grounding and Grammar Induction for Robotic Manipulation Commands. RoboNLP@ACL 2017: 35-43 - [c79]Hanh Tran, David C. Hogg:
Anomaly Detection using a Convolutional Winner-Take-All Autoencoder. BMVC 2017 - [c78]Muhannad Al-Omari, Paul Duckworth, Nils Bore, Majd Hawasly, David C. Hogg, Anthony G. Cohn:
Grounding of Human Environments and Activities for Autonomous Robots. IJCAI 2017: 1395-1402 - [i4]Jawad Tayyub, Majd Hawasly, David C. Hogg, Anthony G. Cohn:
CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations. CoRR abs/1709.03456 (2017) - 2016
- [j27]Kyaw Kyaw Htike, David C. Hogg:
Adapting pedestrian detectors to new domains: A comprehensive review. Eng. Appl. Artif. Intell. 50: 142-158 (2016) - [j26]Feng Gu, Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg, Francisco Flórez-Revuelta, Dorothy Monekosso, Paolo Remagnino:
Weakly supervised activity analysis with spatio-temporal localisation. Neurocomputing 216: 778-789 (2016) - [c77]Paul Duckworth, Yiannis Gatsoulis, Ferdian Jovan, Nick Hawes, David C. Hogg, Anthony G. Cohn:
Unsupervised Learning of Qualitative Motion Behaviours by a Mobile Robot. AAMAS 2016: 1043-1051 - [c76]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Personalizing Human Video Pose Estimation. CVPR 2016: 3063-3072 - [c75]Paul Duckworth, Muhannad Al-Omari, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn:
Unsupervised Activity Recognition Using Latent Semantic Analysis on a Mobile Robot. ECAI 2016: 1062-1070 - [c74]James Charles, Derek R. Magee, David C. Hogg:
Virtual Immortality: Reanimating Characters from TV Shows. ECCV Workshops (3) 2016: 879-886 - [c73]Eris Chinellato, David C. Hogg, Anthony G. Cohn:
Feature Space Analysis for Human Activity Recognition in Smart Environments. Intelligent Environments 2016: 194-197 - [c72]Muhannad Al-Omari, Eris Chinellato, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn:
Unsupervised Grounding of Textual Descriptions of Object Features and Actions in Video. KR 2016: 505-508 - [i3]Nick Hawes, Chris Burbridge, Ferdian Jovan, Lars Kunze, Bruno Lacerda, Lenka Mudrová, Jay Young, Jeremy L. Wyatt, Denise Hebesberger, Tobias Körtner, Rares Ambrus, Nils Bore, John Folkesson, Patric Jensfelt, Lucas Beyer, Alexander Hermans, Bastian Leibe, Aitor Aldoma, Thomas Faulhammer, Michael Zillich, Markus Vincze, Muhannad Al-Omari, Eris Chinellato, Paul Duckworth, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn, Christian Dondrup, Jaime Pulido Fentanes, Tomás Krajník, João Machado Santos, Tom Duckett, Marc Hanheide:
The STRANDS Project: Long-Term Autonomy in Everyday Environments. CoRR abs/1604.04384 (2016) - 2015
- [j25]Krishna Sandeep Reddy Dubba, Anthony G. Cohn, David C. Hogg, Mehul Bhatt, Frank Dylla:
Learning Relational Event Models from Video. J. Artif. Intell. Res. 53: 41-90 (2015) - [c71]Aryana Tavanai, Muralikrishna Sridhar, Eris Chinellato, Anthony G. Cohn, David C. Hogg:
Joint Tracking and Event Analysis for Carried Object Detection. BMVC 2015: 79.1-79.11 - [i2]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Personalizing Human Video Pose Estimation. CoRR abs/1511.06676 (2015) - 2014
- [c70]Jawad Tayyub, Aryana Tavanai, Yiannis Gatsoulis, Anthony G. Cohn, David C. Hogg:
Qualitative and Quantitative Spatio-temporal Relations in Daily Living Activity Recognition. ACCV (5) 2014: 115-130 - [c69]Ardhendu Behera, Anthony G. Cohn, David C. Hogg:
Real-time Activity Recognition by Discerning Qualitative Relationships Between Randomly Chosen Visual Features. BMVC 2014 - [c68]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Upper Body Pose Estimation with Temporal Sequential Forests. BMVC 2014 - [c67]Kyaw Kyaw Htike, David C. Hogg:
Unsupervised Detector Adaptation by Joint Dataset Feature Learning. ICCVG 2014: 270-277 - [c66]Kyaw Kyaw Htike, David C. Hogg:
Weakly supervised pedestrian detector training by unsupervised prior learning and cue fusion in videos. ICIP 2014: 2338-2342 - [c65]Kyaw Kyaw Htike, David C. Hogg:
Efficient Non-iterative Domain Adaptation of Pedestrian Detectors to Video Scenes. ICPR 2014: 654-659 - [c64]Aryana Tavanai, Muralikrishna Sridhar, Feng Gu, Anthony G. Cohn, David C. Hogg:
Context Aware Detection and Tracking. ICPR 2014: 2197-2202 - [c63]Ardhendu Behera, Matthew Chapman, Anthony G. Cohn, David C. Hogg:
Egocentric Activity Recognition using Histograms of Oriented Pairwise Relations. VISAPP (2) 2014: 22-30 - 2013
- [j24]James M. Ferryman, David C. Hogg, Jan Sochman, Ardhendu Behera, José A. Rodríguez-Serrano, Simon F. Worgan, Longzhen Li, Valerie Leung, Murray Evans, Philippe Cornic, Stéphane Herbin, Stefan Schlenger, Michael Dose:
Robust abandoned object detection integrating wide area visual surveillance and social context. Pattern Recognit. Lett. 34(7): 789-798 (2013) - [c62]James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman:
Domain Adaptation for Upper Body Pose Tracking in Signed TV Broadcasts. BMVC 2013 - [c61]Ian Hales, David C. Hogg, Kia Ng, Roger Boyle:
Automated Ground-Plane Estimation for Trajectory Rectification. CAIP (2) 2013: 378-385 - [c60]Aryana Tavanai, Muralikrishna Sridhar, Feng Gu, Anthony G. Cohn, David C. Hogg:
Carried Object Detection and Tracking Using Geometric Shape Models and Spatio-temporal Consistency. ICVS 2013: 223-233 - 2012
- [j23]Hannah M. Dee, Anthony G. Cohn, David C. Hogg:
Building semantic scene models from unconstrained video. Comput. Vis. Image Underst. 116(3): 446-456 (2012) - [j22]Dima Damen, David C. Hogg:
Explaining Activities as Consistent Groups of Events - A Bayesian Framework Using Attribute Multiset Grammars. Int. J. Comput. Vis. 98(1): 83-102 (2012) - [j21]Dima Damen, David C. Hogg:
Detecting Carried Objects from Sequences of Walking Pedestrians. IEEE Trans. Pattern Anal. Mach. Intell. 34(6): 1056-1067 (2012) - [j20]Andrew Zisserman, John M. Winn, Andrew W. Fitzgibbon, Luc Van Gool, Josef Sivic, Christopher K. I. Williams, David C. Hogg:
In Memoriam: Mark Everingham. IEEE Trans. Pattern Anal. Mach. Intell. 34(11): 2081-2082 (2012) - [c59]Ardhendu Behera, David C. Hogg, Anthony G. Cohn:
Egocentric Activity Monitoring and Recovery. ACCV (3) 2012: 519-532 - [c58]Ardhendu Behera, Anthony G. Cohn, David C. Hogg:
Workflow Activity Monitoring Using Dynamics of Pair-Wise Qualitative Spatial Relations. MMM 2012: 196-209 - 2011
- [c57]John Greenall, David C. Hogg, Anthony G. Cohn:
Temporal Structure Models for Event Recognition. BMVC 2011: 1-11 - [c56]Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg:
From Video to RCC8: Exploiting a Distance Based Semantics to Stabilise the Interpretation of Mereotopological Relations. COSIT 2011: 110-125 - [c55]Jan Sochman, David C. Hogg:
Who knows who - Inverting the Social Force Model for finding groups. ICCV Workshops 2011: 830-837 - [c54]Simon F. Worgan, Ardhendu Behera, Anthony G. Cohn, David C. Hogg:
Exploiting petri-net structure for activity classification and user instruction within an industrial setting. ICMI 2011: 113-120 - [c53]Krishna Sandeep Reddy Dubba, Mehul Bhatt, Frank Dylla, David C. Hogg, Anthony G. Cohn:
Interleaved Inductive-Abductive Reasoning for Learning Complex Event Models. ILP 2011: 113-129 - 2010
- [c52]Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg:
Unsupervised Learning of Event Classes from Video. AAAI 2010: 1631-1638 - [c51]Basela Hasan, David C. Hogg:
Segmentation using Deformable Spatial Priors with Application to Clothing. BMVC 2010: 1-11 - [c50]Krishna Sandeep Reddy Dubba, Anthony G. Cohn, David C. Hogg:
Event Model Learning from Complex Videos using ILP. ECAI 2010: 93-98 - [c49]Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg:
Discovering an Event Taxonomy from Video using Qualitative Spatio-temporal Graphs. ECAI 2010: 1103-1104 - [c48]Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg:
Relational Graph Mining for Learning Events from Video. STAIRS 2010: 315-327
2000 – 2009
- 2009
- [j19]Hannah M. Dee, David C. Hogg:
Navigational strategies in behaviour modelling. Artif. Intell. 173(2): 329-342 (2009) - [c47]Dima Damen, David C. Hogg:
Attribute Multiset Grammars for Global Explanations of Activities. BMVC 2009: 1-11 - [c46]Hannah M. Dee, David C. Hogg, Anthony G. Cohn:
Scene Modelling and Classification Using Learned Spatial Relations. COSIT 2009: 295-311 - [c45]Dima Damen, David C. Hogg:
Recognizing linked events: Searching the space of feasible explanations. CVPR 2009: 927-934 - [c44]David C. Hogg:
Motion and Object Class Discovery from Video. VISAPP (1) 2009: 17-19 - 2008
- [j18]Brandon Bennett, Derek R. Magee, Anthony G. Cohn, David C. Hogg:
Enhanced tracking and recognition of moving objects by reasoning about spatio-temporal continuity. Image Vis. Comput. 26(1): 67-81 (2008) - [c43]John Bryden, David C. Hogg, Sita Popat, Mick Wallis:
Building artificial personalities - expressive communication channels based on an interlingua for a human-robot dance. ALIFE 2008: 80-87 - [c42]Moaath Al-Rajab, David C. Hogg, Kia Ng:
A Comparative Study on Using Zernike Velocity Moments and Hidden Markov Models for Hand Gesture Recognition. AMDO 2008: 319-327 - [c41]Muralikrishna Sridhar, Anthony G. Cohn, David C. Hogg:
Learning Functional Object-Categories from a Relational Spatio-Temporal Representation. ECAI 2008: 606-610 - [c40]Dima Damen, David C. Hogg:
Detecting Carried Objects in Short Video Sequences. ECCV (3) 2008: 154-167 - [c39]Roberto Fraile, David C. Hogg, Anthony G. Cohn:
Motion segmentation by consensus. ICPR 2008: 1-4 - [c38]Hannah M. Dee, Roberto Fraile, David C. Hogg, Anthony G. Cohn:
Modelling Scenes Using the Activity within Them. Spatial Cognition 2008: 394-408 - [e3]Anthony G. Cohn, David C. Hogg, Ralf Möller, Bernd Neumann:
Logic and Probability for Scene Interpretation, 24.02. - 29.02.2008. Dagstuhl Seminar Proceedings 08091, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2008 [contents] - [i1]Bernd Neumann, Anthony G. Cohn, David C. Hogg, Ralf Möller:
08091 Abstracts Collection - Logic and Probability for Scene Interpretation. Logic and Probability for Scene Interpretation 2008 - 2007
- [c37]Dima Damen, David C. Hogg:
Associating People Dropping off and Picking up Objects. BMVC 2007: 1-10 - [c36]Mick Wallis, Sita Popat, Alice Bayliss, Joslin McKinney, John Bryden, David C. Hogg, Matthew Godden, Rich Walker:
SpiderCrab and the emergent object: designing for the twenty-first century. DUX 2007: 3 - 2006
- [c35]Anthony G. Cohn, David C. Hogg, Brandon Bennett, Vincent E. Devin, Aphrodite Galata, Derek R. Magee, Chris J. Needham, Paulo E. Santos:
Cognitive Vision: Integrating Symbolic Qualitative Representations with Computer Vision. Cognitive Vision Systems 2006: 221-246 - 2005
- [j17]Chris J. Needham, Paulo E. Santos, Derek R. Magee, Vincent E. Devin, David C. Hogg, Anthony G. Cohn:
Protocols from perceptual observations. Artif. Intell. 167(1-2): 103-136 (2005) - [c34]Hannah M. Dee, David C. Hogg:
On the feasibility of using a cognitive model to filter surveillance data. AVSS 2005: 34-39 - 2004
- [c33]Hannah M. Dee, David C. Hogg:
Detecting inexplicable behaviour. BMVC 2004: 1-10 - [c32]Paulo E. Santos, Derek R. Magee, Anthony G. Cohn, David C. Hogg:
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation. ECAI 2004: 544-548 - [c31]Brandon Bennett, Derek R. Magee, Anthony G. Cohn, David C. Hogg:
Using Spatio-Temporal Continuity Constraints to Enhance Visual Tracking of Moving Objects. ECAI 2004: 922-926 - 2003
- [j16]Vincent E. Devin, David C. Hogg:
Reactive memories: an interactive talking-head. Image Vis. Comput. 21(13-14): 1125-1133 (2003) - [c30]Anthony G. Cohn, Derek R. Magee, Aphrodite Galata, David C. Hogg, Shyamanta M. Hazarika:
Towards an Architecture for Cognitive Vision Using Qualitative Spatio-temporal Representations and Abduction. Spatial Cognition 2003: 232-248 - 2002
- [j15]Neil Johnson, David C. Hogg:
Representation and synthesis of behaviour using Gaussian mixtures. Image Vis. Comput. 20(12): 889-894 (2002) - [c29]Aphrodite Galata, Anthony G. Cohn, Derek R. Magee, David C. Hogg:
Modeling Interaction Using Learnt Qualitative Spatio-Temporal Relations and Variable Length Markov Models. ECAI 2002: 741-745 - 2001
- [j14]Aphrodite Galata, Neil Johnson, David C. Hogg:
Learning Variable-Length Markov Models of Behavior. Comput. Vis. Image Underst. 81(3): 398-413 (2001) - [c28]