Advanced Topics in Computer Vision

✍ Scribed by Martin Weinmann (auth.), Giovanni Maria Farinella, Sebastiano Battiato, Roberto Cipolla (eds.)

• Publisher: Springer-Verlag London
• Year: 2013
• Tongue: English
• Leaves: 437
• Series: Advances in Computer Vision and Pattern Recognition
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages I-XIV
Visual Features—From Early Concepts to Modern Computer Vision....Pages 1-34
Where Next in Object Recognition and how much Supervision Do We Need?....Pages 35-64
Recognizing Human Actions by Using Effective Codebooks and Tracking....Pages 65-93
Evaluating and Extending Trajectory Features for Activity Recognition....Pages 95-111
Co-recognition of Images and Videos: Unsupervised Matching of Identical Object Patterns and Its Applications....Pages 113-141
Stereo Matching—State-of-the-Art and Research Challenges....Pages 143-179
Visual Localization for Micro Aerial Vehicles in Urban Outdoor Environments....Pages 181-214
Moment Constraints in Convex Optimization for Segmentation and Tracking....Pages 215-242
Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets....Pages 243-276
Top–Down Bayesian Inference of Indoor Scenes....Pages 277-311
Efficient Loopy Belief Propagation Using the Four Color Theorem....Pages 313-339
Boosting k -Nearest Neighbors Classification....Pages 341-375
Learning Object Detectors in Stationary Environments....Pages 377-409
Video Temporal Super-resolution Based on Self-similarity....Pages 411-430
Back Matter....Pages 431-433

✦ Subjects

Computer Imaging, Vision, Pattern Recognition and Graphics