The 2010 edition of the European Conference on Computer Vision was held in Heraklion, Crete. The call for papers attracted an absolute record of 1,174 submissions. We describe here the selection of the accepted papers: Thirty-eight area chairs were selected coming from Europe (18), USA and Canada (16), and Asia (4). Their selection was based on the following criteria: (1) Researchers who had served at least two times as Area Chairs within the past two years at major vision conferences were excluded; (2) Researchers who served as Area Chairs at the 2010 Computer Vision and Pattern Recognition were also excluded (exception: ECCV 2012 Program Chairs); (3) Minimization of overlap introduced by Area Chairs being former student and advisors; (4) 20% of the Area Chairs had never served before in a major conference; (5) The Area Chair selection process made all possible efforts to achieve a reasonable geographic distribution between countries, thematic areas and trends in computer vision. EachArea Chair was assigned by the Program Chairs between 28–32 papers. Based on paper content, the Area Chair recommended up to seven potential reviewers per paper. Such assignment was made using all reviewers in the database including the conflicting ones. The Program Chairs manually entered the missing conflict domains of approximately 300 reviewers. Based on the recommendation of the Area Chairs, three reviewers were selected per paper (with at least one being of the top three suggestions), with 99.
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(5) The Area Chair selection process made all possible efforts to achieve a reasonable geographic distribution between countries, thematic areas and trends in computer vision.
Visual Learning.- Constrained Spectral Clustering via Exhaustive and Efficient Constraint Propagation.- Object Recognition with Hierarchical Stel Models.- MIForests: Multiple-Instance Learning with Randomized Trees.- Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations.- Stacked Hierarchical Labeling.- Spotlights and Posters R2.- Fully Isotropic Fast Marching Methods on Cartesian Grids.- Clustering Complex Data with Group-Dependent Feature Selection.- On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation.- Exploring the Identity Manifold: Constrained Operations in Face Space.- Multi-label Linear Discriminant Analysis.- Convolutional Learning of Spatio-temporal Features.- Learning Pre-attentive Driving Behaviour from Holistic Visual Features.- Detecting People Using Mutually Consistent Poselet Activations.- Disparity Statistics for Pedestrian Detection: Combining Appearance, Motion and Stereo.- Multi-stage Sampling with Boosting Cascades for Pedestrian Detection in Images and Videos.- Learning to Detect Roads in High-Resolution Aerial Images.- Thinking Inside the Box: Using Appearance Models and Context Based on Room Geometry.- A Structural Filter Approach to Human Detection.- Geometric Constraints for Human Detection in Aerial Imagery.- Handling Urban Location Recognition as a 2D Homothetic Problem.- Recursive Coarse-to-Fine Localization for Fast Object Detection.- A Local Bag-of-Features Model for Large-Scale Object Retrieval.- Velocity-Dependent Shutter Sequences for Motion Deblurring.- Colorization for Single Image Super Resolution.- Programmable Aperture Camera Using LCoS.- A New Algorithmic Approach for Contrast Enhancement.- Seeing through Obscure Glass.- A Continuous Max-Flow Approach to Potts Model.- Hybrid Compressive Sampling via a New Total Variation TVL1.- Perspective Imaging under Structured Light.- Lighting and Pose Robust Face Sketch Synthesis.- Predicting Facial Beauty without Landmarks.- Gabor Feature Based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary.- Motion Profiles for Deception Detection Using Visual Cues.- A Robust and Scalable Approach to Face Identification.- Emotion Recognition from Arbitrary View Facial Images.- Face Liveness Detection from a Single Image with Sparse Low Rank Bilinear Discriminative Model.- Robust Head Pose Estimation Using Supervised Manifold Learning.- Knowledge Based Activity Recognition with Dynamic Bayesian Network.- View and Style-Independent Action Manifolds for Human Activity Recognition.- Figure-Ground Image Segmentation Helps Weakly-Supervised Learning of Objects.- Enhancing Interactive Image Segmentation with Automatic Label Set Augmentation.- Hough Transform and 3D SURF for Robust Three Dimensional Classification.
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Produktdetaljer

ISBN
9783642155666
Publisert
2010-08-30
Utgiver
Vendor
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet