Abstract:
In this letter, we propose a robust and real-time visual tracking algorithm via a novel kernel based multiple cue adaptive appearance model (KBMCAAM). In particular, the ...Show MoreMetadata
Abstract:
In this letter, we propose a robust and real-time visual tracking algorithm via a novel kernel based multiple cue adaptive appearance model (KBMCAAM). In particular, the appearance model is constructed with a naive Bayes classifier which is trained utilizing sparse multi-scale Haar-like features weighted by a spatial kernel function. Moreover, multiple image cues are integrated to improve the model's discriminative capacity. Experimental results demonstrate the superior performance of our proposed method to many state-of-art algorithms.
Published in: IEEE Signal Processing Letters ( Volume: 20, Issue: 11, November 2013)