Mean-shift object tracking through 4-D scale space

The scale self-adaptive mechanism is one of the promising research directions in the object tracking issue based on mean-shift. A typical method is to adopt Lindeberg's scale-space theory to obtain the scale information of the target. However, the 2-D scale vector is reduced to 1-D in the existing algorithm. So it is not precise enough to portray the changing state of the object scale under affine transformation, which greatly limits the scope of application of the method. Hence, the 1-D filter in the scale dimension is extended to 2-D in this paper. Correspondingly, the 4-D scale space is constructed, then the problem is mapped into two interleaved mean-shift procedure in the spatial and scale dimension through scale space. The modified algorithm achieves the effective object tracking in spatial position and scale direction simultaneously, which enhances the self adaptability when the target scale is changing, and expands the scope of application of the algorithm.