Signal Processing: Image Communication, Vol. 38, pp. 151-166, 2015Anass Nouri, Christophe Charrier, Olivier Lézoray
Normandie Université, UNICAEN, ENSICAEN, GREYC UMR CNRS 6072, Caen, FRANCE
Our visual attention is attracted by specific areas into 3D objects (repre- sented by meshes). This visual attention depends on the degree of saliency exposed by these areas. In this paper, we propose a novel multi-scale ap- proach for detecting salient regions. To do so, we define a local surface descriptor based on patches of adaptive size and filled in with a local height field. The single-scale saliency of a vertex is defined as its degree measure in the mesh with edges weights computed from adaptive patch similarities weighted by the local curvature. Finally the multi-scale saliency is defined as the average of single-scale saliencies weighted by their respective entropies. The contribution of the multi-scale aspect is analyzed and showed through the different results. The strength and the stability of our approach with re- spect to noise and simplification are also studied. Our approach is compared to the state-of-the-art and presents competitive results.
This work received funding from the Agence Nationale de la Recherche, ANR-14-CE27-0001 GRAPHSIP.