Fundamentals of interactive computer graphics
Fundamentals of interactive computer graphics
Tracking and data association
Stereoscopic tracking of bodies in motion
Image and Vision Computing - Special issue: 5th Alvey vision meeting
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Integrated Person Tracking Using Stereo, Color, and Pattern Detection
International Journal of Computer Vision - Special issue on a special section on visual surveillance
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
Gesture recognition using the Perseus architecture
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maintaining Multi-Modality through Mixture Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Real-Time Wide Area Multi-Camera Stereo Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
People detection and tracking using stereo vision and color
Image and Vision Computing
Real-time multiple people tracking using competitive condensation
Pattern Recognition
Tracking multiple people with recovery from partial and total occlusion
Pattern Recognition
Multiple-person tracker with a fixed slanting stereo camera
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Sequential Monte Carlo methods for multiple target tracking anddata fusion
IEEE Transactions on Signal Processing
Visual capture and understanding of hand pointing actions in a 3-D environment
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive Multifeature Tracking in a Particle Filtering Framework
IEEE Transactions on Circuits and Systems for Video Technology
Multi-camera people tracking using evidential filters
International Journal of Approximate Reasoning
People detection and tracking with multiple stereo cameras using particle filters
Journal of Visual Communication and Image Representation
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
Particle filtering with multiple and heterogeneous cameras
Pattern Recognition
Shape from pairwise silhouettes for plan-view map generation
Image and Vision Computing
Ambient sensor system for freezing of gait detection by spatial context analysis
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
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This work proposes a novel approach for people detection and tracking in colour-with-depth sequences using a particle filtering approach. Detection and tracking are performed in plan-view maps integrating occupancy and height information with a novel plan-view map representation for colour information. Using the three maps, we propose a multiple particle filtering algorithm for people detection and tracking. The observation model proposed integrates information from the three maps so that people with different coloured clothes are not confused even when they interact at close distances. To avoid the coalescence problem when people with similar coloured clothes approach each other, the weight of particles is modified by an interaction factor that combines colour and position information. The algorithm also avoids the coalescence problem in case of total occlusion by means of an occlusion detection and recovering mechanism. Finally, a solution is proposed to improve the exponential complexity of multiple particle filters so that the algorithm proposed has linear complexity. The approach proposed has been tested in several colour-with-depth sequences where people move and interact freely in the environment. In the sequences, people walk at different distances, cross their paths causing frequent occlusions, jump, run and have close interactions such as shaking hands or embracing each other. The experimental results show that our proposal is able to detect and keep track of every person with a low error and deals with partial and total occlusions. Besides, the detection and tracking techniques presented are appropriate for large tracking problems in real-time applications since their complexity is linear, are suitable for parallel processing and allow the integration of information provided by multiple stereo vision sensors.