Abstract: In visual target tracking and localization, the target could not be located due to the lack of features or the severe occlusion. Aiming at this, an algorithm based on confidence evaluation of neighboring targets is designed. In the tracking process, by detecting and extracting the marker features of neighboring targets, and combining the Hamming distance of each feature marker and the normalized result with respect to other markers as well as the probability of occurrence of each marker, the final confidence of each marker is obtained. The marker with the maximum confidence is to used determine the target location. Experimental results show that the algorithm can greatly improve the robustness and accuracy of tracking during occlusion or target features missing.

Key words: target tracking and localization, proximity marking, confidence evaluation, Hamming distance