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Subspace segmentation is the task of segmenting data lying on multiple linear subspaces. Its applications in computer vision include motion segmentation in video, structure-from-motion, and image clustering. In this work, we describe a novel approach for subspace segmentation that uses probabilistic inference via a message-passing algorithm. We cast the(More)
This paper presents a general method for the integration of distributed microphone arrays for localization of a sound source. The recently proposed sound localization technique, known as SRP-PHAT, is shown to be a special case of the more general microphone array integration mechanism presented here. The proposed technique utilizes spatial likelihood(More)
A new approach to sound localization, known as enhanced sound localization, is introduced, offering two major benefits over state-of-the-art algorithms. First, higher localization accuracy can be achieved compared to existing methods. Second, an estimate of the source orientation is obtained jointly, as a consequence of the proposed sound localization(More)
—This paper introduces a mechanism for localizing a microphone array when the location of sound sources in the environment is known. Using the recently proposed spatial observ-ability function (SOF) based microphone array integration technique , a maximum likelihood estimator for the correct position and orientation of the array is derived. This is used to(More)
In this paper, we present a large database of over 50,000 user-labeled videos collected from YouTube. We develop a compact representation called "tiny videos" that achieves high video compression rates while retaining the overall visual appearance of the video as it varies over time. We show that frame sampling using affinity propagation-an exemplar-based(More)
This paper proposes a new technique for face detection and lip feature extraction. A real-time field-programmable gate array (FPGA) implementation of the two proposed techniques is also presented. Face detection is based on a naive Bayes classifier that classifies an edge-extracted representation of an image. Using edge representation significantly reduces(More)
The Uncapacitated Facility Location Problem (UFLP) is one of the most widely studied discrete location problems, whose applications arise in a variety of settings. We tackle the UFLP using probabilistic inference in a graphical model-an approach that has received little attention in the past. We show that the fixed points of max-product linear programming(More)
A multiple microphone time varying filter that is an extension of the dual-microphone speech enhancement technique of [7] is proposed and experimentally analyzed. The technique utilizes information regarding the locations of the speech source of interest and the microphones to compute a time varying filter that results in substantial noise reduction over(More)
A variational inference algorithm for robust speech separation , capable of recovering the underlying speech sources even in the case of more sources than microphone observations , is presented. The algorithm is based upon an gen-erative probabilistic model that fuses time-delay of arrival (TDOA) information with prior information about the speakers and(More)