In this paper, we propose a method to detect removed or stolen objects in complex environments robustly and efficiently
based on the multi-cue adaptive fusion. In this method, the target observation is represented by multiple cues. When
fusing each cue, a fusion scheme based on fuzzy logic has been developed. To solve the problem raised by part
occlusions, target object is divided into multiple sub-parts and subsequently matching of at least one sub-part between
current fields and initial model leads to a final decision that the target object is safe. Furthermore this method can
distinguish target object into stolen or occluded objects by analyzing the matching degree of sub-parts with their initial
models. Experimental results have demonstrated the effectiveness of the proposed method.
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