Self-closed partial shape descriptor for shape retrieval
Huijie Fan, Yang Cong, Yandong Tang · 2012
We propose a discriminative partial-based algorithm for shape recognition and retrieval. A key distinction of our approach is that we use pairwise geometric relations between contour fragments containing important and salient shape information to establish self-closed partial descriptor (SCPD), it can capture similar local parts in matching shape contours and meanwhile overcome part occlusion and distortion. We establish local coordinate system for each fragment to make sure SCPD is invariant to RST (rotation, scaling, and translation) transformation. In the matching stage, a scale approximation scheme is used to get rid of invalid matches. We experiment on MPEG7 shape database, and experimental results illustrate that our algorithm performs well on shape retrieval.