Video Search and Mining

1. Front Matter

   PDF

2. Motion Trajectory Analysis

   1. Front Matter

      Pages 1-1

      PDF

   2. Object Trajectory Analysis in Video Indexing and Retrieval Applications

      • Mattia Broilo, Nicola Piotto, Giulia Boato, Nicola Conci, Francesco G. B. De Natale

      Pages 3-32

   3. Trajectory Clustering for Scene Context Learning and Outlier Detection

      • Nadeem Anjum, Andrea Cavallaro

      Pages 33-51

   4. Motion Trajectory-Based Video Retrieval, Classification, and Summarization

      • Xiang Ma, Xu Chen, Ashfaq Khokhar, Dan Schonfeld

      Pages 53-82

3. High-Dimensional Video Representation

   1. Front Matter

      Pages 83-83

      PDF

   2. Three Dimensional Information Extraction and Applications to Video Analysis

      • Arturo Donate, Xiuwen Liu

      Pages 85-114

   3. Statistical Analysis on Manifolds and Its Applications to Video Analysis

      • Pavan Turaga, Ashok Veeraraghavan, Anuj Srivastava, Rama Chellappa

      Pages 115-144

4. Semantic Video Analysis

   1. Front Matter

      Pages 145-145

      PDF

   2. Semantic Video Content Analysis

      • Massimiliano Albanese, Pavan Turaga, Rama Chellappa, Andrea Pugliese, V. S. Subrahmanian

      Pages 147-176

   3. Video Genre Inference Based on Camera Capturing Models

      • Ping-Hao Wu, Sanjay Purushotham, C. -C. Jay Kuo

      Pages 177-201

   4. Visual Concept Learning from Weakly Labeled Web Videos

      • Adrian Ulges, Damian Borth, Thomas M. Breuel

      Pages 203-232

5. Personalized Video

   1. Front Matter

      Pages 233-233

      PDF

   2. Face Recognition and Retrieval in Video

      • Caifeng Shan

      Pages 235-260

   3. A Human-Centered Computing Framework to Enable Personalized News Video Recommendation

      • Hangzai Luo, Jianping Fan

      Pages 261-281

6. Video Mining

   1. Front Matter

      Pages 283-283

      PDF

   2. A Holistic, In-Compression Approach to Mining Independent Motion Segments for Massive Surveillance Video Collections

      • Zhongfei (Mark) Zhang, Haroon Khan

      Pages 285-303

   3. Video Repeat Recognition and Mining by Visual Features

      • Xianfeng Yang, Qi Tian

      Pages 305-326

   4. Mining TV Broadcasts 24/7 for Recurring Video Sequences

      • Ina Döhring, Rainer Lienhart

      Pages 327-356

   5. YouTube Scale, Large Vocabulary Video Annotation

      • Nicholas Morsillo, Gideon Mann, Christopher Pal

      Pages 357-386

As cameras become more pervasive in our daily life, vast amounts of video data are generated. The popularity of YouTube and similar websites such as Tudou and Youku provides strong evidence for the increasing role of video in society. One of the main challenges confronting us in the era of information technology is to - fectively rely on the huge and rapidly growing video data accumulating in large multimedia archives. Innovative video processing and analysis techniques will play an increasingly important role in resolving the difficult task of video search and retrieval. A wide range of video-based applications have benefited from - vances in video search and mining including multimedia information mana- ment, human-computer interaction, security and surveillance, copyright prot- tion, and personal entertainment, to name a few. This book provides an overview of emerging new approaches to video search and mining based on promising methods being developed in the computer vision and image analysis community. Video search and mining is a rapidly evolving discipline whose aim is to capture interesting patterns in video data. It has become one of the core areas in the data mining research community. In comparison to other types of data mining (e. g. text), video mining is still in its infancy. Many challenging research problems are facing video mining researchers.

• Video Retrieval
• calculus
• classification
• clustering
• cognition
• computational intelligence
• computer vision
• data mining
• image analysis
• information extraction
• intelligence
• learning
• statistical analysis
• video mining

• Multimedia Communications Laboratory Department of Electrical & Computer Engineering, University of Illinois at Chicago, Chicago, USA

  Dan Schonfeld

• Philips Research, Eindhoven, The Netherlands

  Caifeng Shan

• Department of Computing, Hong Kong Polytechnic University, Kowloon,Hong Kong, China

  Dacheng Tao

• Department of Computer Science, University of Bath, United Kingdom

  Liang Wang

Policies and ethics