Robust Multi-Pedestrian Tracking in Thermal-Visible Surveillance Videos

Robust Multi-Pedestrian Tracking in Thermal-Visible Surveillance Videos

Robust Multi-Pedestrian Tracking in Thermal-Visible Surveillance Videos

Spector, Lincoln, Contributing Editor has reference to this Academic Journal, PHwiki organized this Journal Robust Multi-Pedestrian Tracking in Thermal-Visible Surveillance VideosAlex Leykin, Yang Ran, in addition to Riad HammoudGoalCreate a pedestrian tracker that operates in:Varying illumination conditionsCrowded environmentTo achieve it we create a fusion pedestrian tracker that uses input from:IR cameraRGB cameraOur approach consists of three stages:BG SubtractionBayesian trackerPedestrian ClassifierRelated WorkFusion background model:Y.Owechko, S.Medasani, in addition to N.Srinivasa “Classifier swarms as long as human detection in infrared imagery”, OTCBVS 2004M.Yasuno, N.Yasuda, in addition to M.Aoki “Pedestrian detection in addition to tracking in far infrared images” OTCBVS 2004C. Dai, Y. Zheng, X. Li “Layered Representation as long as Pedestrian Detection in addition to Tracking in Infrared Imagery” OTCBVS 2005J.Davis, V.Sharma “Fusion-based Background Subtraction Using Contour Saliency”, OTCBVS 2005 Bayesian as long as mulation:J. Deutscher, B. North, B. Bascle in addition to A. Blake “Tracking through singularities in addition to discontinuities by r in addition to om sampling”, ICCV 1999A. Elgammal in addition to L. S. Davis, “Probabilistic Framework as long as Segmenting People Under Occlusion”, ICCV 2001. M. Isard, J. MacCormick, “BraMBLe: a Bayesian multiple-blob tracker”, ICCV 2001T. Zhao, R. Nevatia “Tracking Multiple Humans in Crowded Environment”, CVPR 2004

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Background ModelTwo stacks of codeword values (codebooks)

Spector, Lincoln PC World Contributing Editor

Spector, Lincoln Contributing Editor

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