Computer Vision -- ECCV 2014

13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I

AvDavid Fleet,Tomas Pajdla

Häftad, Engelska, 2014

Del 8689 i serien Lecture Notes in Computer Science

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Beskrivning

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. computational photography and low-level vision; motion and 3D scene analysis;

Produktinformation

Utgivningsdatum:2014-09-22
Mått:155 x 235 x 48 mm
Vikt:1 311 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:853
Förlag:Springer International Publishing AG
ISBN:9783319105895

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Visual Tracking by Sampling Tree-Structured Graphical Models.- Tracking Interacting Objects Optimally Using Integer Programming.- Learning Latent Constituents for Recognition of Group Activities in Video.- Large-Scale Object Classification Using Label Relation Graphs.- 30Hz Object Detection with DPM V5.- Knowing a Good HOG Filter when You See It: Efficient Selection of Filters for Detection.- Linking People in Videos with “Their” Names Using Coreference Resolution.- Optimal Essential Matrix Estimation via Inlier-Set Maximization.- UPnP: An Optimal O(n) Solution to the Absolute Pose Problem with Universal Applicability.- 3D Reconstruction of Dynamic Textures in Crowd Sourced Data.- 3D Interest Point Detection via Discriminative Learning.- Pose Locality Constrained Representation for 3D Human Pose Reconstruction.- Synchronization of Two Independently Moving Cameras without Feature Correspondences.- Multi Focus Structured Light for ecovering Scene Shape and Global Illumination.- Coplanar Common Points in Non-centric Cameras.- SRA: Fast Removal of General Multipath for ToF Sensors.- Sub-pixel Layout for Super-Resolution with Images in the Octic Group.- Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition.- Read My Lips: Continuous Signer Independent Weakly Supervised Viseme Recognition.- Multilinear Wavelets: A Statistical Shape Space for Human Faces.- Distance Estimation of an Unknown Person from a Portrait.- Probabilistic Temporal Head Pose Estimation Using a Hierarchical Graphical Model.- Description-Discrimination Collaborative Tracking.- Online, Real-Time Tracking Using a Category-to-Individual Detector.- Robust Visual Tracking with Double Bounding Box Model.- Tractable and Reliable Registration of 2D Point Sets.- Graduated Consistency-Regularized Optimization for Multi-graph Matching.- Optical Flow Estimation with Channel Constancy.- Non-local Total Generalized Variation for Optical Flow Estimation.- Learning Brightness Transfer Functions for the Joint Recovery of Illumination Changes and Optical Flow.- Hipster Wars: Discovering Elements of Fashion Styles.- From Low-Cost Depth Sensors to CAD: Cross-Domain 3D Shape Retrieval via Regression Tree Fields.- Fast and Accurate Texture Recognition with Multilayer Convolution and Multifractal Analysis.- Learning to Rank 3D Features.- Salient Color Names for Person Re-identification.- Learning Discriminative and Shareable Features for Scene Classification.- Image Retrieval and Ranking via Consistently Reconstructing Multi-attribute Queries.- Neural Codes for Image Retrieval.- Architectural Style Classification Using Multinomial Latent Logistic Regression.- Instance Segmentation of Indoor Scenes Using a Coverage Loss.- Superpixel Graph Label Transfer with Learned Distance Metric.- Precision-Recall-Classification Evaluation Framework: Application to Depth Estimation on Single Images.- A Multi-stage Approach to Curve Extraction.- Geometry Driven Semantic Labeling of Indoor Scenes.- A Novel Topic-Level Random Walk Framework for Scene Image Co-segmentation.- Surface Matching and Registration by Landmark Curve-Driven Canonical Quasiconformal Mapping.- Activity Group Localization by Modeling the Relations among Participants.- Finding Coherent Motions and Semantic Regions in Crowd Scenes: A Diffusion and Clustering Approach.- Semantic Aware Video Transcription Using Random Forest Classifiers.- Ranking Domain-Specific Highlights by Analyzing Edited Videos.- A Multi-transformational Model for Background Subtraction with Moving Cameras.- Visualizing and Understanding Convolutional Networks.- Part-Based R-CNNs for Fine-Grained Category Detection.