LDA based color information fusion for visual objects tracking
Fei Qi, Xiaowei Song, Guangming Shi · 2009
In this paper, an approach for object tracking is proposed based on the online color information fusion scheme. The fusion scheme, is performed by projecting multi-channel color images to a one-dimensional pseudo gray scale space. This dimensionality reduction simplifies the designation of the tracking algorithm. The fusing coefficients are determined by taking the Fisher linear discriminant analysis to maximize the discriminative capability after taking the projection. The robustness of the approach lies in exploiting the appearance discrimination of the object in cluttered scenarios with varying illumination conditions. This scheme is embedded into a mean-shift tracking system and the experimental results show our scheme can enhance the discriminant characters in the changing environment and hence producing robust tracking results.