Vision-based hand pose estimation through similarity search using the earth mover's distance

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Vision-based hand pose estimation through similarity search using the earth mover's distance

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Vision-based hand pose estimation presents unique challenges, particularly if high-fidelity reconstruction is desired. Searching large databases of synthetic pose candidates for items similar to the input offers an attractive means of attaining this goal. The earth mover's distance is a perceptually meaningful measure of dissimilarity that has shown great promise in content-based image retrieval. It is in general, however, a computationally expensive operation and must be used sparingly. The authors investigate a way of economising on its use while preserving much of its accuracy when applied naively in the context of searching for hand pose candidates in large synthetic databases. In particular, a two-tier search method is proposed which achieves similar accuracy with a speed increase of two orders of magnitude. The system performance is evaluated using real input and the results obtained using the different approaches are compared.

Inspec keywords: computer vision; image retrieval; performance evaluation; pose estimation; content-based retrieval; image reconstruction

Other keywords: large synthetic databases; vision-based hand pose estimation; contour-based similarity search; computationally expensive operation; system performance evaluation; two-tier search method; earth mover distance; large database searching; high-fidelity reconstruction; content-based image retrieval; synthetic pose candidates

Subjects: Computer vision and image processing techniques; Image recognition; Information retrieval techniques

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