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...
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
Abstract. This paper deals, for the first time, with an analysis of localization capabilities of weakly supervised categorization systems. Most existing categorization approaches ...
Abstract. In this paper we introduce a new representation for shapebased object class detection. This representation is based on very sparse and slightly flexible configurations of...
A common design of an object recognition system has
two steps, a detection step followed by a foreground withinclass
classification step. For example, consider face detection
by...