Advanced Topics in Computer Vision (eBook)

Giovanni Maria Farinella, Sebastiano Battiato, Roberto Cipolla (Herausgeber)

eBook Download: PDF

2013 | 2013
XIV, 433 Seiten
Springer London (Verlag)
978-1-4471-5520-1 (ISBN)

Infos

This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.

Dr. Giovanni Maria Farinella is Adjunct Professor of Computer Science at the University of Catania, Italy, and Contract Professor of Computer Vision at the School of Arts of Catania, Italy. Dr. Sebastiano Battiato is Associate Professor at the University of Catania, Italy. Dr. Roberto Cipolla is Professor of Information Engineeringat the University of Cambridge, UK.

Inhalt

Visual Features: From Early Concepts to Modern Computer VisionMartin WeinmannWhere Next in Object Recognition and How Much Supervision Do We Need?Sandra Ebert and Bernt SchieleRecognizing Human Actions by Using Effective Codebooks and TrackingLamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini and Alberto Del BimboEvaluating and Extending Trajectory Features for Activity RecognitionRoss Messing, Atousa Torabi, Aaron Courville and Chris PalCo-Recognition of Images and Videos: Unsupervised Matching of Identical Object Patterns and its ApplicationsMinsu Cho, Young Min Shin and Kyoung Mu LeeStereo Matching: State-of-the-Art and Research ChallengesMichael Bleyer and Christian BreitenederVisual Localization for Micro Aerial Vehicles in Urban Outdoor EnvironmentsAndreas Wendel and Horst BischofMoment Constraints in Convex Optimization for Segmentation and TrackingMaria Klodt, Frank Steinbrücker and Daniel CremersLarge Scale Metric Learning for Distance-Based Image Classification on Open Ended Data SetsThomas Mensink, Jakob Verbeek, Florent Perronnin and Gabriela CsurkaTop-Down Bayesian Inference of Indoor ScenesLuca Del Pero and Kobus BarnardEfficient Loopy Belief Propagation Using the Four Color TheoremRadu Timofte and Luc Van GoolBoosting k-Nearest Neighbors ClassificationPaolo Piro, Richard Nock, Wafa Bel Haj Ali, Frank Nielsen and Michel BarlaudLearning Object Detectors in Stationary EnvironmentsPeter M. Roth, Sabine Sternig and Horst BischofVideo Temporal Super-Resolution Based on Self-SimilarityMihoko Shimano, Takahiro Okabe, Imari Sato and Yoichi Sato

Produkt-Details

• Erscheint lt. Verlag: 24.9.2013
• Reihe/Serie: Advances in Computer Vision and Pattern Recognition
• Reihe/Serie: Advances in Computer Vision and Pattern Recognition
• Zusatzinfo: XIV, 433 p. 218 illus., 180 illus. in color.
• Verlagsort: London
• Sprache: englisch
• Themenwelt: Informatik ► Grafik / Design ► Digitale Bildverarbeitung
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: 3D Reconstruction • Boosting • computer vision • Convex Optimization • Event and Activity Recognition • graph cuts • Image and video analysis • Image Segmentation • Large Scale Image Classification • learning objects • Loopy Belief Propagation • Message Parsing • metric learning • Object detection • Scene Understanding • Stereo Matching • super resolution • Visual Features
• ISBN-10: 1-4471-5520-3 / 1447155203
• ISBN-13: 978-1-4471-5520-1 / 9781447155201