Computer Vision -- ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5-9, 2012, Revised Selected Papers, Part III [Paperback]

The four-volume set LNCS 7724--7727 constitutes the thoroughly refereed post-conference proceedings of the 11th Asian Conference on Computer Vision, ACCV 2012, held in Daejeon, Korea, in November 2012.The total of 226 contributions presented in these volumes was carefully reviewed and selected from 869 submissions. The papers are organized in topical sections on object detection, learning and matching; object recognition; feature, representation, and recognition; segmentation, grouping, and classification; image representation; image and video retrieval and medical image analysis; face and gesture analysis and recognition; optical flow and tracking; motion, tracking, and computational photography; video analysis and action recognition; shape reconstruction and optimization; shape from X and photometry; applications of computer vision; low-level vision and applications of computer vision.Oral Session 6: Optical Flow and Tracking.- Adaptive Integration of Feature Matches into Variational Optical Flow Methods.- Efficient Learning of Linear Predictors Using Dimensionality Reduction.- Robust Visual Tracking Using Dynamic Classifier Selection with SparseRepresentation of Label Noise.- Poster Session 6: Motion, Tracking, andComputational Photography Dynamic Objectness for Adaptive Tracking.- Visual Tracking in Continuous Appearance Space via Sparse Coding.- Robust Object Tracking in Crowd Dynamic Scenes Using ExplicitStereo Depth.- Structured Visual Tracking with Dynamic Graph.- Online Multi-target Tracking by Large Margin Structured Learning.- An Anchor Patch Based Optimization Framework for Reducing Optical Flow Drift in Long Image Sequences.- One-Class Multiple Instance Learning and Applications to Target Tracking.- Dense Scene Flow Based on Depth and Multi-channel Bilateral Filter.- Object Tracking within the Framework of Concept Drift.- Multiple Target Tracking Using Frame Triplets.- Spatio-Temporal Clustering Model for Multi-object Tracking throughOcclusions.- Robusl³