Methods based on local, viewpoint invariant features have proven capable of recognizing objects in spite of viewpoint changes, occlusion and clutter. However, these approaches fail...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
For object recognition under varying illumination conditions, we propose a method based on photometric alignment. The photometric alignment is known as a technique that models bot...
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...
This paper presents a new structure-based interest region detector called Principal Curvature-Based Regions (PCBR) which we use for object class recognition. The PCBR interest ope...
Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas ...