Modeling a dynamic environment using a Bayesian multiple hypothesis approach
Artificial Intelligence
Visual surveillance in a dynamic and uncertain world
Artificial Intelligence - Special volume on computer vision
Eye finding via face detection for a foveated, active vision system
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A System for Person-Independent Hand Posture Recognition against Complex Backgrounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Object Localisation in Images
International Journal of Computer Vision
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Towards Robust Multi-cue Integration for Visual Tracking
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
Learning the Statistics of People in Images and Video
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Object Detection Using the Statistics of Parts
International Journal of Computer Vision
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Democratic Integration: Self-Organized Integration of Adaptive Cues
Neural Computation
Feature-centric evaluation for efficient cascaded object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Improving object classification in far-field video
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
An unsupervised, online learning framework for moving object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Contour grouping with prior models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic target recognition organized via jump-diffusion algorithms
IEEE Transactions on Image Processing
Editorial: ECOVISION: Challenges in Early-Cognitive Vision
International Journal of Computer Vision
Human Tracking by IP PTZ Camera Control in the Context of Video Surveillance
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Fuzzy Feature-Based Upper Body Tracking with IP PTZ Camera Control
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
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We address the problem of localizing and obtaining high-resolution footage of the people present in a scene. We propose a biologically-inspired solution combining pre-attentive, low-resolution sensing for detection with shiftable, high-resolution, attentive sensing for confirmation and further analysis.The detection problem is made difficult by the unconstrained nature of realistic environments and human behaviour, and the low resolution of pre-attentive sensing. Analysis of human peripheral vision suggests a solution based on integration of relatively simple but complementary cues. We develop a Bayesian approach involving layered probabilistic modeling and spatial integration using a flexible norm that maximizes the statistical power of both dense and sparse cues. We compare the statistical power of several cues and demonstrate the advantage of cue integration. We evaluate the Bayesian cue integration method for human detection on a labelled surveillance database and find that it outperforms several competing methods based on conjunctive combinations of classifiers (e.g., Adaboost). We have developed a real-time version of our pre-attentive human activity sensor that generates saccadic targets for an attentive foveated vision system. Output from high-resolution attentive detection algorithms and gaze state parameters are fed back as statistical priors and combined with pre-attentive cues to determine saccadic behaviour. The result is a closed-loop system that fixates faces over a 130 deg field of view, allowing high-resolution capture of facial video over a large dynamic scene.