Facial motion tracking from fine to coarse

A modified general matching method is proposed for tracking moving points on a talking face. Contradictory to the early algorithms in this area, we begin the search from the finest level. If the texture information at the finest level is not sufficient for point tracking, we let the included texture information “grow” to the coarse level step by step. With this fine-to-coarse “growing” method, the searching templates are adapted to the texture information surrounding the tracked points. This procedure can reduce mismatches due to texture insufficiency in the coarse-to-fine procedure. It can also reduce the interference from unrelated points. Although, we emphasize the searching direction change, the main idea of this approach is to let the tracking templates “grow” from the smallest scale to a larger scale according to the texture information surrounding the tracked points. This approach is more adaptive compared with the traditional fixed template tracking. The procedure employs Gabor wavelet feature vectors, and examples illustrate the gains from this approach