We propose the use of 3D (2D+time) Shape Context to recognize the spatial and temporal details inherent in human actions. We represent an action in a video sequence by a 3D point ...
Franziska Meier, Irfan A. Essa, Matthias Grundmann
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
This paper presents a methodology for learning taxonomic relations from a set of documents that each explain one of the concepts. Three different feature extraction approaches with...
—We investigate the problem of retrieving similar shapes from a large database; in particular, we focus on medical tumor shapes (“Find tumors that are similar to a given patter...
In this paper, we propose a salient object extraction method using the contrast map and salient points for object-based image retrieval. In order to make the contrast map, we gener...