Similarity search in texts, notably in biological sequences, has received substantial attention in the last few years. Numerous filtration and indexing techniques have been create...
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
In this work, we focus on fast and efficient recognition of motions in multi-attribute continuous motion sequences. 3D motion capture data, animation motion data, and sensor data ...
We present a novel method for tracking objects by combining density matching with shape priors. Density matching is a tracking method which operates by maximizing the Bhattacharyy...
We introduce a new domain-independent framework for formulating and efficiently evaluating similarity queries over historical data, where given a history as a sequence of timestam...