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In this paper, we present a method of creating domain-based multiple descriptions of images and video. These descriptions are created by partitioning the transform domain of the signal into sets whose points are maximally separated from each other. This property enables simple error concealment methods to produce good estimates of lost signal samples. We(More)
In this paper, we present an adaptive maximum a posteriori (MAP) error concealment algorithm for dispersively packetized wavelet-coded images. We model the subbands of a wavelet-coded image as Markov random fields, and use the edge characteristics in a particular subband, and regularity properties of subband/wavelet samples across scales, to adapt the(More)
—A home-based intelligent energy conservation system needs to know what appliances (or loads) are being used in the home and when they are being used in order to provide intelligent feedback or to make intelligent decisions. This analysis task is known as load disaggregation or non-intrusive load monitoring (NILM). The datasets used for NILM research(More)
—We study the problem of dividing the 2 lattice into partitions so that minimal intra-partition distance between the points is maximized. We show that this problem is analogous to the problem of sphere packing. An upper bound on the achievable intra-partition distances for a given number of partitions follows naturally from this observation, since the(More)
Despite the recent progress in both pixel-domain and compressed-domain video object tracking, the need for a tracking framework with both reasonable accuracy and reasonable complexity still exists. This paper presents a method for tracking moving objects in H.264/AVC-compressed video sequences using a spatio-temporal Markov random field (ST-MRF) model. An(More)
Attention retargeting in images is a concept in which the content or composition of the image is altered in an effort to guide the viewer's attention to a specific location. In this paper, we propose a method that modifies the color of a selected region in an image to increase its saliency and draw attention towards it. To avoid many of the issues present(More)
—Nonintrusive load monitoring (NILM) is a process of discerning what appliances are running within a house from processing the power or current signal of a smart meter. Since appliance states are not observed directly, hidden Markov models (HMM) are a natural choice for modelling NILM appliances. However, because the number of HMM states grows rapidly with(More)
this paper, we investigate the effect of path correlation on video communications when path-diversity routing techniques are employed together with forward error correction (FEC). We study the statistical properties of packet losses when correlation between paths exists and demonstrate that the effects of path correlation on received video quality depend on(More)