We present an algorithm for producing behavior descriptions of planar fixed axes mechanical motions from image sequences using a formal behavior language. The language, which covers the most important class of mechanical motions, symbolically captures the qualitative aspects of objects that translate and rotate along axes that are fixed in space. The algorithm exploits the structure of these motions to robustly recover the objects behaviors. It starts by identifying the independently moving objects, their motion parameters, and their variation with respect to time using normal optical flow analysis, iterative motion segmentation, and motion parameter estimation. It then produces a formal description of their behavior by identifying individual uniform motion events and simultaneous motion changes, and parsing them with a motion grammar. We demonstrate the algorithm on three sets of image sequences: mechanisms, everyday situations, and a robot manipulation scenario.
Bibliographical noteFunding Information:
Leo Joskowicz is supported in part by grant 98/536 from the Israeli Academy of Science, by a grant from the Authority for Research and Development, The Hebrew University of Jerusalem, Israel, and by a Ford University Research Grant, the Ford ADAPT2000 project.