In this paper, we propose a memory, space, and time efficient framework to scale distributional similarity to the web. We exploit sketch techniques, especially the Count-Min sketch, which approximates the frequency of an item in the corpus without explicitly storing the item itself. These methods use hashing to deal with massive amounts of the streaming text. We store all item counts computed f...

This paper presents a novel representation for human actions which encodes the variations in the shape and motion of the performing actor. When an actor performs an action, at each time instant, the outer object boundary is projected to the image plane as a 2D contour. A sequence of such contours forms a 3D volume in the spatiotemporal space. The differential geometric analysis of the volume su...

Image-based approaches to sketch recognition typically cast sketch recognition as a machine learning problem. In systems that adopt image-based recognition, the collected ink is generally fed through a standard three stage pipeline consisting of the feature extraction, learning and classification steps. Although these approaches make regular use of machine learning, existing work falls short of...

Article history: Received 13 August 2014 Received in revised form 11 July 2015 Accepted 27 November 2015 Available online 22 January 2016 Sketch retrieval aims at retrieving the most similar sketches from a large database based on one hand-drawn query. Successful retrieval hinges on an effective representation of sketch images and an efficient searchmethod. In this paper, we propose a represent...