In this paper, a novel motion-based active video indexing scheme is proposed for videos acquired from active visual systems. With the foveate wavelet transform as the representation of active videos, the description for the object of primary interest during smooth pursuit can be generated in the foveal area based on the behavior of the motion field estimated by a two-pass motion estimation MRF-MAP algorithm. Afterwards, a vector of 36 numbers is generated as the index for the object. Furthermore, the attention shift camera motion can be detected by use of this motion field, which is employed as another important indicator of the video contents. The efficacy of this active object-based video indexing scheme is demonstrated through extensive experiments.
['Jie Wei', 'Ze-Nian Li', 'Izidor Gertner']
A novel motion-based active video indexing method