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Multiobject tracking in video using a trisection paradigm

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Abstract

This paper proposes a technique for analyzing the following three problems: (a) segmentation of moving objects, (b) feature extraction, and (c) the solution of the correspondence problem in multiobject tracking in video sequences. In (c), we use a paradigm to solve the correspondence problem and to determine a motion trajectory based on a trisectional structure. The paradigm distinguishes between real-world objects, extracts image features such as motion blobs and color patches, and abstracts objects such as meta objects that denote real-world physical objects. The efficiency of the proposed method for determining the motion trajectories of moving objects will be demonstrated in this paper on the basis of the analysis of real image sequences that are subjected to severe disturbances (e.g., increasing congestion, shadow casting, and lighting transitions).

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Authors and Affiliations

  1. Institute for Electronics, Signal Processing and Communications, Otto von Guericke University Magdeburg, D-39016, Magdeburg, P.O. Box 4120, Germany

    A. K. Al-Hamadi, R. Niese & B. Michaelis

Authors
  1. A. K. Al-Hamadi
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  2. R. Niese
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  3. B. Michaelis
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Correspondence to A. K. Al-Hamadi.

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The text was submitted by the authors in English.

Ayoub K. Al-Hamadi received his Masters Degree (Dipl.-Ing.) in Electrical Engineering and Information Technology in 1997 and his PhD in Technical Computer Science at the Otto von Guericke University of Magdeburg, Germany, in 2001. Since 2002, he has been Assistant Professor at the Institute for Electronics, Signal Processing, and Communications Technology at the University of Magdeburg. His research work concentrates on the field of image processing, tracking analysis, and pattern recognition. Dr. Al-Hamadi is the author of more than 22 articles.

Robert Niese received his Masters Degree (Dipl.-Ing.) in Computer Science at the University of Magdeburg, Germany, in 2004. He is currently working on a PhD thesis focusing on image processing, tracking, and pattern recognition.

Bernd Michaelis was born in Magdeburg, Germany, in 1947. He received a Masters Degree in Electronic Engineering from the Technische Hochschule Magdeburg in 1971 and his first PhD in 1974. Between 1974 and 1980 he worked at the Technische Hochschule Magdeburg and was granted a second doctoral degree in 1980. In 1993, he became Professor of Technical Computer Science at the Otto von Guericke University of Magdeburg. His research work concentrates on the field of image processing, artificial neural networks, pattern recognition, processor architectures, and microcomputers. Professor Michaelis is the author of more than 150 papers.

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Al-Hamadi, A.K., Niese, R. & Michaelis, B. Multiobject tracking in video using a trisection paradigm. Pattern Recognit. Image Anal. 17, 493–507 (2007). https://doi.org/10.1134/S1054661807040086

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