TY - GEN
T1 - Learning the behavior of users in a public space through video tracking
AU - Yan, Wei
AU - Forsyth, D. A.
PY - 2005
Y1 - 2005
N2 - The paper describes a video tracking system that tracks and analyzes the behavioral pattern of users in a public space. We have obtained important statistical measurements about users' behavior, which can be used to evaluate architectural design in terms of human spatial behavior and model the behavior of users in public spaces. Previously, such measurements could only be obtained through costly manual processes, e.g. behavioral mapping and time-lapse filming with human examiners. Our system has automated the process of analyzing the behavior of users. The system consists of a head detector for detecting people in each single frame of the video and data association for tracking people through frames. We compared the results obtained using our system with those obtained by manual counting, for a small data set, and found the results to be fairly accurate. We then applied the system to a large-scale data set and obtained substantial statistical measurements of parameters such as the total number of users who entered the space, the total number of users who sat by a fountain, the time that each spent by the fountain, etc. These statistics allow fundamental rethinking of the way people use a public space This research is a novel application of computer vision in evaluating architectural design in terms of human behavior.
AB - The paper describes a video tracking system that tracks and analyzes the behavioral pattern of users in a public space. We have obtained important statistical measurements about users' behavior, which can be used to evaluate architectural design in terms of human spatial behavior and model the behavior of users in public spaces. Previously, such measurements could only be obtained through costly manual processes, e.g. behavioral mapping and time-lapse filming with human examiners. Our system has automated the process of analyzing the behavior of users. The system consists of a head detector for detecting people in each single frame of the video and data association for tracking people through frames. We compared the results obtained using our system with those obtained by manual counting, for a small data set, and found the results to be fairly accurate. We then applied the system to a large-scale data set and obtained substantial statistical measurements of parameters such as the total number of users who entered the space, the total number of users who sat by a fountain, the time that each spent by the fountain, etc. These statistics allow fundamental rethinking of the way people use a public space This research is a novel application of computer vision in evaluating architectural design in terms of human behavior.
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U2 - 10.1109/ACVMOT.2005.67
DO - 10.1109/ACVMOT.2005.67
M3 - Conference contribution
AN - SCOPUS:35348906710
SN - 0769522718
SN - 9780769522715
T3 - Proceedings - Seventh IEEE Workshop on Applications of Computer Vision, WACV 2005
SP - 370
EP - 377
BT - Proceedings - Seventh IEEE Workshop on Applications of Computer Vision, WACV 2005
PB - IEEE Computer Society
T2 - 7th IEEE Workshop on Applications of Computer Vision, WACV 2005
Y2 - 5 January 2005 through 7 January 2005
ER -