Salient view selection based on sparse representation

Yi-Chen Chen, Vishal M. Patel, Rama Chellappa, P. Jonathon Phillips

Abstract: A sparse representation-based approach is proposed to find the salient views of 3D objects. Under the assumption that a meaningful object can appear in several perceptible views, we build the object's approximate convex shape that exhibits these apparent views. The salient views are categorized into two groups. The first are boundary representative views that have several visible sides and object surfaces attractive to human perceivers. The second are side representative views that best represent views from sides of the approximating convex shape. The side representative views are class-specific views that possess the most representative power compared to other within-class views. Using the concept of characteristic view class, we first present a sparse representation-based approach for estimating the boundary representative views. With the estimated boundaries, we determine the side representative view(s) based on a minimum reconstruction error.