Davis ajainumdeduabhinavgcscmuedumdrodriguezmitreorglsdcsumdedu Abstract How should a video be represented We propose a new representation for videos based on midlevel discriminative spatiotemporal patches These spatiotemporal patches might correspo
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Representing Videos using Midlevel Discriminative Patches Arpit Jain Abhinav Gup
Presentation on theme: "Representing Videos using Midlevel Discriminative Patches Arpit Jain Abhinav Gup"— Presentation transcript:
Davis ajainumdeduabhinavgcscmuedumdrodriguezmitreorglsdcsumdedu Abstract How should a video be represented We propose a new representation for videos based on midlevel discriminative spatiotemporal patches These spatiotemporal patches might correspo ID: 3565 Download Pdf
Agenda. Beyond Fixed . Keypoints. Beyond . Keypoints. Open discussion. Part Discovery from Partial Correspondence. [. Subhransu. . Maji. and Gregory . Shakhnarovich. , CVPR 2013]. K. eypoints. in diverse categories.
Efros Carnegie Mellon University Pittsburgh PA 15213 USA httpgraphicscscmueduprojectsdiscriminativePatches Abstract The goal of this paper is to discover a set of discriminative patches which can serve as a fully unsupervised midlevel visual repre s
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In this paper we investigate scalable techniques for inducing discriminative features by taking ad vantage of simple second order structure in the data We focus on multiclass classi64257cation and show that features extracted from the generalized ei
Given a new you want to predict its class The generative iid approach to this problem posits a model family xc c 1 and chooses the best parameters 955 by maximizing or integrating over the joint distribution where denotes the data D c 2 An
Abhinav S Bhatele and Laxmikant V Kale. Parallel Programming Laboratory, UIUC. IS. TOPOLOGY IMPORTANT AGAIN?. E-mail: bhatele, kale @ illinois.edu. Webpage: http://charm.cs.uiuc.edu. Outline. May 29th, 2009.
University of Illinois at Urbana-Champaign. Abhinav Bhatele, Eric Bohm, Laxmikant V. Kale. Parallel Programming Laboratory. Euro-Par 2009. Outline. Motivation. Solution: Mapping of OpenAtom. Performance Benefits.
IT 530, Lecture Notes. Introduction: Complete and over-complete bases. Signals are often represented as a linear combination of basis functions (e.g. Fourier or wavelet representation).. The basis functions always have the same dimensionality as the (discrete) signals they represent..
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