Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: A Real Time System for Detecting and Tracking People
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Hydra: Multiple People Detection and Tracking Using Silhouettes
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Counting People from Multiple Cameras
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Counting Crowded Moving Objects
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Estimating crowd density with Minkowski fractal dimension
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Issues and solutions in surveillance camera placement
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
RVM-based human action classification in crowd through projection and star skeletonization
Journal on Image and Video Processing - Special issue on video-based modeling, analysis, and recognition of human motion
Measurement of pedestrians in urban environment using subtraction stereo
INSS'09 Proceedings of the 6th international conference on Networked sensing systems
Local empirical templates and density ratios for people counting
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Detection of human groups in videos
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
A corpus for benchmarking of people detection algorithms
Pattern Recognition Letters
A Reliable People Counting System via Multiple Cameras
ACM Transactions on Intelligent Systems and Technology (TIST)
Visual knowledge transfer among multiple cameras for people counting with occlusion handling
Proceedings of the 20th ACM international conference on Multimedia
Accurate pedestrian counting system based on local features
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Segmentation of Pedestrians with Confidence Level Computation
Journal of Signal Processing Systems
People counting by learning their appearance in a multi-view camera environment
Pattern Recognition Letters
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The goal of this work is to provide a system which can aid in monitoring crowded urban environments, which often contain tight groups of people. In this paper, we consider the problem of counting the number of people in the scene and also tracking them reliably. We propose a novel method for detecting and estimating the count of people in groups, dense or otherwise, as well as tracking them. Using prior knowledge obtained from the scene and accurate camera calibration, the system learns the parameters required for estimation. This information can then be used to estimate the count of people in the scene, in real-time. Groups are tracked in the same manner as individuals, using Kalman filtering techniques. Favorable results are shown for groups of various sizes moving in an unconstrained fashion.