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Dynamic image sequence analysis using fuzzy measures.

Z Q Liu¹, L T Bruton, J C Bezdek

¹Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 5, 2008

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This study introduces an image understanding system that uses fuzzy logic to track moving objects in dynamic sequences. The system effectively handles vague object definitions and movements for natural interpretation, demonstrated in complex traffic scenes.

Area of Science:

Computer Vision
Artificial Intelligence
Image Processing

Background:

Traditional image interpretation systems struggle with the inherent uncertainties in dynamic scenes.
Moving objects often have ill-defined shapes and trajectories, posing challenges for precise tracking.

Purpose of the Study:

To develop an advanced image understanding system capable of accurately tracking moving objects in dynamic image sequences.
To address the challenge of vague object definitions and dynamic activities using fuzzy logic.

Main Methods:

Implementation of a symbolic object-oriented image interpretation system.
Application of a novel three-dimensional (3-D) recursive filter with a time-varying frequency-planar passband.
Integration of fuzzy measures to manage uncertainties and capture subtle variations in object data.

Related Experiment Videos

Main Results:

The system successfully tracks moving objects in complex real-world traffic scenes.
Fuzzy measures effectively handle the vagueness associated with object shapes and trajectories.
The image understanding system produces natural and accurate outputs.

Conclusions:

The proposed fuzzy set and fuzzy measure-based image understanding system offers a robust solution for tracking in dynamic, uncertain environments.
This approach enhances the naturalness and accuracy of image interpretation, particularly in challenging scenarios like traffic monitoring.