Model-based recognition of articulated objects
This paper presents a model-based matching technique for recognition of articulated objects (with two parts) and the poses of these parts in synthetic aperture radar (SAR) images. Using articulation invariants as features, the recognition system first hypothesizes the pose of the larger part and then the pose of the smaller part. Geometric reasoning is carried out to correct identification errors. The thresholds for the quality of match are determined dynamically by minimizing the probability of a random match for the recognition system. Results are presented using both occluded synthetic articulated object SAR signatures and actual signatures of articulated objects from the real-world data. The system performance is evaluated with respect to identification performance and accuracy of estimates for the poses of the object parts.
articulated objects object recognition sar images