An approach to estimate the information of moving objects is described in terms of their kinetic and static properties such as 2D velocity, acceleration, position, and the size of each object for the features of motion snd shape. To obtain the information of motion/shape of multiple objects, an advanced contour matching scheme is developed, which includes the synthesis of edge images and the analysis of object shape with a high matching confidence as well as a low computation cost. The scheme is composed of three algorithms: a motion estimation by an iterative triple cross-correlation, an image synthesis by shifting and masking the object, and a shape analysis for determining the object size. Implementing fuzzy membership functions to the object shape, the scheme gets improved in accuracy of capturing motion and shape of multiple moving objects. Experimental result shows that the proposed method is valid for several walking men in real scene.

This paper describes an adaptive sensing system with tracking and zooming a moving object in the stable environment. Both the close contour matching technique and the effective determination of zoom ratio by fuzzy control are proposed for achieving the sensing system. First, the estimation of object feature parameters, 2-dimensional velocity and size, is based on close contour matching. The correspondence problem is solved with cross-correlation in projections extracted from object contours in the specialized difference images. In the stable environment, these contours matching, capable of eliminating occluded contours or random noises as well as background, works well without heavy-cost optical flow calculation. Next, in order to zoom the tracked object in accordance with the state of its shape or movement practically, fuzzy control is approached first. Three sets of input membership function--the confidence of object shape, the variance of object velocity, and the object size--are evaluated with the simplified implementation. The optimal focal length is achieved of not only desired size but safe tracking in combination with fuzzy rule matrix constituted of membership functions. Experimental results show that the proposed system is robust and valid for numerous kind of moving object in real scene with system period 1.85 sec.