Object tracking based on projective modular active shape model

Abstract

Boundary contour tracking is useful in the field of visual analysis such as motion estimation and 3-D reconstruction. Because active contour model, {\\it Snake}, is fast and easy, it has been used widely in the tracking. Tracking performance depends on stable preservation of correspondence relation and the robustness to the local minima around targets. However, {\\it Snake} is weak and sensitive to noises and local minima because it is edge-based tracking system. This paper shows that active shape model can be appliable to track two dimensional objects while containing their shape information in it. The point distribution models(PDMs) are generated projectively in consideration of projective relations of camera system to world coordinates. For each PDM analysis, the corresponding eigenvector is obtained, which contains contour variational information in image space due to camera motion. Then active shape model is modularly composed of these eigenvectors to construct the projective modular active shape model(MASM). This model has capabilities to cover contour motion generated by camera 6-DOF motion and to overcome edge noises. Moreover, it is of good performance in preserving correspondence relations since including boundary shape as a model and its variational information. The feasibilities are shown by the experimental result on the object tracking for 100 image frames, captured in hand-held motion, with strong edge disturbances around target.