Computer Vision - ACCV 2012 [electronic resource] : 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5-9, 2012, Revised Selected Papers, Part III / edited by Kyoung Mu Lee, Yasuyuki Matsushita, James M. Rehg, Zhanyi Hu.
Contributor(s): Lee, Kyoung Mu [editor.] | Matsushita, Yasuyuki [editor.] | Rehg, James M [editor.] | Hu, Zhanyi [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Computer Science: 7726Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XXVI, 741 p. 336 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642374319.Subject(s): Computer science | Health informatics | Artificial intelligence | Image processing | Pattern recognition | Computer Science | Image Processing and Computer Vision | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Health InformaticsAdditional physical formats: Printed edition:: No titleDDC classification: 006.6 | 006.37 Online resources: Click here to access onlineOral 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 Sparse Representation of Label Noise -- Poster Session 6: Motion, Tracking, and Computational Photography Dynamic Objectness for Adaptive Tracking -- Visual Tracking in Continuous Appearance Space via Sparse Coding -- Robust Object Tracking in Crowd Dynamic Scenes Using Explicit Stereo 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 through Occlusions -- Robust Object Tracking Using Constellation Model with Superpixel -- Robust Registration-Based Tracking by Sparse Representation with Model Update -- Robust and Efficient Pose Estimation from Line Correspondences -- Nonlocal Spectral Prior Model for Low-Level Vision -- Simultaneous Multiple Rotation Averaging Using Lagrangian Duality -- Observation-Driven Adaptive Differential Evolution for Robust Bronchoscope 3-D Motion Tracking -- Tracking Growing Axons by Particle Filtering in 3D + t Fluorescent Two-Photon Microscopy Images -- Image Upscaling Using Multiple Dictionaries of Natural Image Patches -- A Biologically Motivated Double-Opponency Approach to Illumination Invariance -- Measuring Linearity of Closed Curves and Connected Compound Curves -- Patch Mosaic for Fast Motion Deblurring -- Single-Image Blind Deblurring for Non-uniform Camera-Shake Blur -- Image Super-Resolution Using Local Learnable Kernel Regression -- MRF-Based Blind Image Deconvolution -- Efficient Image Appearance Description Using Dense Sampling Based Local Binary Patterns -- Navigation toward Non-static Target Object Using Footprint Detection Based Tracking -- Single Image Super Resolution Reconstruction in Perturbed Exemplar Sub-space -- Image Super-Resolution: Use of Self-learning and Gabor Prior -- Oral Session 7: Video Analysis and Action -- Recognition Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram -- Alpha-Flow for Video Matting -- Combinational Subsequence Matching for Human Identification from General Actions -- Poster Session 7: Video Analysis and Action Recognition Iterative Semi-Global Matching for Robust Driver Assistance Systems -- Action Recognition Using Canonical Correlation Kernels -- A New Framework for Background Subtraction Using Multiple Cues -- Weighted Interaction Force Estimation for Abnormality Detection in Crowd Scenes -- Egocentric Activity Monitoring and Recovery -- Spatiotemporal Salience via Centre-Surround Comparison of Visual Spacetime Orientations -- Temporal-Spatial Refinements for Video Concept Fusion -- Features with Feelings-Incorporating User Preferences in Video Categorization -- A Comparative Study of Encoding, Pooling and Normalization Methods for Action Recognition -- Dynamic Saliency Models and Human Attention: A Comparative Study on Videos -- Horror Video Scene Recognition Based on Multi-view Multi-instance Learning -- Learning Object Appearance from Occlusions Using Structure and Motion Recovery -- Exploring the Similarities of Neighboring Spatiotemporal Points for Action Pair Matching -- Sequential Reconstruction Segment-Wise Feature Track and Structure Updating Based on Parallax Paths -- Generic Active Appearance Models Revisited -- Tracking Pedestrian with Multi-component Online Deformable Part-Based Model -- Local Distance Comparison for Multiple-shot People Re-identification -- Non-sequential Multi-view Detection, Localization and Identification of People Using Multi-modal Feature Maps -- Full 6DOF Pose Estimation from Geo-Located Images -- Learning a Quality-Based Ranking for Feature Point Trajectories.
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.
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