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Proceedings Paper

Robot vision system for pedestrian-flow detection
Author(s): Yuan Y. Tang; Yean J. Lu; Ching Y. Suen
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Paper Abstract

Traffic and transportation engineers continually require a more accurate and large amount of pedestrian flow data for numerous purposes. For example, the increasing use of pedestrian facilities such as building complexes, shopping malls, and airports in densely populated cities demands pedestrian flow data for planning, design, operation, and monitoring of these facilities. Currently, measurement of pedestrian flow data is often performed manually. This paper proposes a robot vision system to measure the number and walking direction of pedestrians using difference image and shape reconstruction techniques. The system consists of eight steps: (1) conversion of video images, (2) digitization of frozen frames, (3) conversion of 256-grey-level images into bilevel images, (4) extraction of rough sketch of pedestrian using difference images, (5) removal of line-noise, (6) reconstruction of shape of the pedestrian, (7) measurement of the number of pedestrians, and (8) determination of the direction of pedestrian movement. In this system, the operations in each step depend only on local information. Thus, they can be performed independently in parallel. A very large scale integration architecture can be implemented in this system to speed up calibration. The accuracy in measuring the number of pedestrians and their direction of travel is about 93% and 92%, respectively.

Paper Details

Date Published: 30 April 1992
PDF: 12 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57959
Show Author Affiliations
Yuan Y. Tang, Concordia Univ. (Canada)
Yean J. Lu, Concordia Univ. (Canada)
Ching Y. Suen, Concordia Univ. (Canada)

Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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