In its full generality, motion analysis of crowded objects necessitates recognition and segmentation of each moving entity. The difficulty of these tasks increases considerably wi...
Background subtraction is a widely used paradigm to detect moving objects in video taken from a static camera and is used for various important applications such as video surveill...
In this paper we discuss object detection when only a small number of training examples are given. Specifically, we show how to incorporate a simple prior on the distribution of n...
Shape is an important cue for generic object recognition but can be insufficient without other cues such as object appearance. We explore a number of ways in which the geometric a...
A meaningful affinity measure between pixels is essential for many computer vision and image processing applications. We propose an algorithm that works in the features' hist...
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework tha...
Given a dense set of imperfect normals obtained by photometric stereo or shape from shading, this paper presents an optimization algorithm which alternately optimizes until conver...
Integration of goal-driven, top-down attention and image-driven, bottom-up attention is crucial for visual search. Yet, previous research has mostly focused on models that are pur...
We apply a biologically inspired model of visual object recognition to the multiclass object categorization problem. Our model modifies that of Serre, Wolf, and Poggio. As in that...