As robots become more ubiquitous, it is increasingly important for untrained users to be able to interact with them intuitively. In this work, we investigate how people refer to objects in the world during relatively unstructured communication with robots. We collect a corpus of deictic interactions from users describing objects, which we use to train language and gesture models that allow our ...

Efficient encoding of motion residuals is essential for low-delay video applications in which videos are encoded by hybrid motion compensation and a residual encoding structure. Current standard video coding systems use hybrid motion compensation and the discrete cosine transform (DCT), where the number of bases needed to encode a residual block is the same as the number of the pixels in the bl...

Matching Pursuit decompositions have been employed for signal coding. For this purpose, Matching Pursuit coefficients need to be quantized. However, their behavior has been shown to be chaotic in some cases; posing difficulties to their modeling and quantizer design. In this work, a different approach is presented. Instead of trying to model the statistics of Matching Pursuit coefficients, the ...

This paper describes how Matching Pursuit can be employed in an MPEG-4 video encoder as a replacement for the DCT at boundary-blocks to improve coding efficiency, while retaining backward compatibility. The key aspect of Matching Pursuit is that the video signal can be represented with less coefficients than with an orthogonal transform, due to the over-complete set of basis functions. However,...

Sparse signal expansions represent or approximate a signal using a small number of elements from a large collection of elementary waveforms. Finding the optimum sparse expansion is known to be NP hard in general and non-optimal strategies such as Matching Pursuit, Orthogonal Matching Pursuit, Basis Pursuit and Basis Pursuit De-noising are often called upon. These methods show good performance i...