This paper presents a new method for viewpoint invariant pedestrian recognition problem. We use a metric learning framework to obtain a robust metric for large margin nearest neigh...
Mert Dikmen, Emre Akbas, Thomas S. Huang, Narendra...
Many conventional human detection methods use features based on gradients, such as histograms of oriented gradients (HOG), but human occlusions and complex backgrounds make accurat...
Abstract. This paper describes a method for topology-free shape morphing based on region cluster-based Earth Mover's Distance (EMD) flows, since existing methods for closed cu...
Part Models Pablo Sala1 , Diego Macrini2 , and Sven Dickinson1 1 University of Toronto, 2 Queen's University Abstract. In recent work [1], we introduced a framework for modelr...
Estimating the atmospheric or meteorological visibility distance is very important for air and ground transport safety, as well as for air quality. However, there is no holistic ap...
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...
Abstract. Scene categorization is an important mechanism for providing high-level context which can guide methods for a more detailed analysis of scenes. State-of-the-art technique...
Estimating planar projective transform (homography) from a pair of images is a classical problem in computer vision. In this paper, we propose a novel algorithm for direct register...
Image segmentation plays an important role in many medical imaging systems, yet in complex circumstances it is still a challenging problem. Among many difficulties, problem caused ...
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...