Shape geodesics for boundary-based object recognition and retrieval

In this paper we define a distance between shapes based on geodesics in shape space. The proposed distance, robust to outliers, uses shape matching to compare shapes locally. Multiscale analysis is introduced in order to avoid problems of local and global variabilities. The resulting similarity measure is invariant to translation, rotation and scaling independently of constraints or landmarks, but constraints can be added to the approach formulation when needed. An evaluation of the proposed approach is reported for shape classification and retrieval on a complex benchmark shape database. It demonstrates in both cases that previous work is outperformed.