Paper
21 March 1989 Automatic Tracking Of Multiple Objects
Andrew Bernat, Stephen Riter
Author Affiliations +
Abstract
We are developing a computer vision system to automatically detect and track human motion across the international border between the United States and Mexico. Fundamental requirements are that the system work in real time under varying environmental conditions with relatively inexpensive hardware. The work we describe is applicable to a wide range of multiple object tracking problems. This paper describes the algorithm we have developed to detect and track moving objects. The algorithm is based on the notion of path coherence. However, the algorithm presented there is not suitable for our application because it requires noise free images, all trajectories must be present from the first through last images, and it requires multiple passes throught the trajectory points as each new image is acquired. This procedure is not acceptable for real time applications. We have previously reported on the front end of our system which takes video images and determines the areas which represent changing objects'. Thus the input to the tracking portion of the system consists of a binary image representing the changing pixels. In this paper we present a detailed description of the tracking algorithm, its implementation in Smalltalk-80, and samples of its operation. We also discuss system performance as a function of trajectory complexity and image noise level.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrew Bernat and Stephen Riter "Automatic Tracking Of Multiple Objects", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); https://doi.org/10.1117/12.969263
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KEYWORDS
Motion detection

Computing systems

Electroluminescence

Detection and tracking algorithms

Automatic tracking

Cameras

Algorithm development

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