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Toward Category-Level Object Recognition

Toward Category-Level Object Recognition (Paperback)

Martial Hebert, Jean Ponce, Cordelia Schmid (엮은이)
Springer-Verlag New York Inc
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Toward Category-Level Object Recognition
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책 정보

· 제목 : Toward Category-Level Object Recognition (Paperback) 
· 분류 : 외국도서 > 컴퓨터 > 컴퓨터 비전/패턴 인식
· ISBN : 9783540687948
· 쪽수 : 620쪽
· 출판일 : 2006-12-22

목차

Object Recognition in the Geometric Era: A Retrospective.- Dataset Issues in Object Recognition.- Industry and Object Recognition: Applications, Applied Research and Challenges.- Recognition of Specific Objects.- What and Where: 3D Object Recognition with Accurate Pose.- Object Recognition Using Local Affine Frames on Maximally Stable Extremal Regions.- 3D Object Modeling and Recognition from Photographs and Image Sequences.- Video Google: Efficient Visual Search of Videos.- Simultaneous Object Recognition and Segmentation by Image Exploration.- Recognition of Object Categories.- Comparison of Generative and Discriminative Techniques for Object Detection and Classification.- Synergistic Face Detection and Pose Estimation with Energy-Based Models.- Generic Visual Categorization Using Weak Geometry.- Components for Object Detection and Identification.- Cross Modal Disambiguation.- Translating Images to Words for Recognizing Objects in Large Image and Video Collections.- A Semi-supervised Learning Approach to Object Recognition with Spatial Integration of Local Features and Segmentation Cues.- Towards the Optimal Training of Cascades of Boosted Ensembles.- Visual Classification by a Hierarchy of Extended Fragments.- Shared Features for Multiclass Object Detection.- Generative Models for Labeling Multi-object Configurations in Images.- Object Detection and Localization Using Local and Global Features.- The Trace Model for Object Detection and Tracking.- Recognition of Object Categories with Geometric Relations.- A Discriminative Framework for Texture and Object Recognition Using Local Image Features.- A Sparse Object Category Model for Efficient Learning and Complete Recognition.- Object Recognition by Combining Appearance and Geometry.- Shape Matching and Object Recognition.- An Implicit Shape Model for Combined Object Categorization and Segmentation.- Statistical Models of Shape and Texture for Face Recognition.- Joint Recognition and Segmentation.- Image Parsing: Unifying Segmentation, Detection, and Recognition.- Sequential Learning of Layered Models from Video.- An Object Category Specific mrf for Segmentation.

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