Efficient retrieval of deformed and occluded shapes

We propose an approach for matching deformed and occluded shapes using dynamic programming. Our algorithms handle noise and shape distortions by allowing matching of merged sequences of consecutive small segments in a shape, with larger segments of another shape, while being invariant to translation, scale and orientation transformations of shapes. We illustrate the effectiveness of our algorithms in retrieval of shapes on two different two-dimensional datasets: one of static hand gesture shapes and another of marine life shapes