2014/07/08 by Mohamed H. Dridi, Dridi, Mohamed H.
Computer Science · Engineering · Physics and Astronomy · #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Remote-Sensing Image Classification #Video Surveillance and Tracking Methods #cs.CV #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1407.2044
20 pages, 17 figures, correction of some references
openalex publication_date 2014/07/08 · arxiv created 2014/08/07 · arxiv updated 2014/08/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we present a number of methods (manual, semi-automatic and automatic) for tracking individual targets in high density crowd scenes where thousand of people are gathered. The necessary data about the motion of individuals and a lot of other physical information can be extracted from consecutive image sequences in different ways, including optical flow and block motion estimation. One of the famous methods for tracking moving objects is the block matching method. This way to estimate subject motion requires the specification of a comparison window which determines the scale of the estimate. In this work we present a real-time method for pedestrian recognition and tracking in sequences of high resolution images obtained by a stationary (high definition) camera located in different places on the Haram mosque in Mecca. The objective is to estimate pedestrian velocities as a function of the local density.The resulting data of tracking moving pedestrians based on video sequences are presented in the following section. Through the evaluated system the spatio-temporal coordinates of each pedestrian during the Tawaf ritual are established. The pilgrim velocities as function of the local densities in the Mataf area (Haram Mosque Mecca) are illustrated and very precisely documented.