This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
Understanding shapes has been a challenging issue for many years, firstly motivated by computer vision and more recently by many complex applications in diverse fields, such as me...
Marco Attene, Silvia Biasotti, Michela Mortara, Gi...
This paper proposes a novel graph matching algorithm based on skeletons and applies it to shape recognition based on object silhouettes. The main idea is to match the critical poin...
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Path planning is an active topic in the literature, and efficient navigation over non-planar surfaces is an open research question. In this work we present a novel technique for ...
Rafael P. Torchelsen, Luiz F. Scheidegger, Guilher...