Neural network combination by fuzzy integral for robust change detection in remotely sensed imagery
EURASIP Journal on Applied Signal Processing
Representation of occurrences for road vehicle traffic
Artificial Intelligence
Reflections on cognitive vision systems
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
A visitor counter system using fuzzy measure theory and boosting method
WSEAS Transactions on Information Science and Applications
Particle swarm optimization for determining fuzzy measures from data
Information Sciences: an International Journal
Estimation of fuzzy measures using covariance matrices in Gaussian mixtures
Applied Computational Intelligence and Soft Computing
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In this paper, we present an image understanding system using fuzzy sets and fuzzy measures. This system is based on a symbolic object-oriented image interpretation system. We apply a simple, powerful three-dimensional (3-D) recursive filter to tracking moving objects in a dynamic image sequence. This filter has a time-varying 3-D frequency-planar passband that is adapted in a feedback system to automatically track moving objects. However, as objects in the image sequence are not well-defined and are engaged in dynamic activities, their shapes and trajectories in most cases can be described only vaguely. In order to handle these uncertainties, we use fuzzy measures to capture subtle variations and manage the uncertainties involved. This enables us to develop an image understanding system that produces a very natural output. We demonstrate the effectiveness of our system with complex real traffic scenes