We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
In recent years many powerful Computer Vision algorithms have been invented, making automatic or semiautomatic solutions to many popular vision tasks, such as visual object recogn...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
We present a shape matching algorithm based on the chamfer distance transform which can be easily integrated into the well-known SIFT framework. The shape matching was designed to...
— Image keypoints are broadly used in robotics for different purposes, ranging from recognition to 3D reconstruction, passing by SLAM and visual servoing. Robust keypoint matchin...