TY  - BOOK
AU  - Huang,Yongzhen
AU  - Tan,Tieniu
ED  - SpringerLink (Online service)
TI  - Feature Coding for Image Representation and Recognition
T2  - SpringerBriefs in Computer Science,
SN  - 9783662450000
AV  - Q337.5 
U1  - 006.4 23
PY  - 2014///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Computer science
KW  - Computer software
KW  - Artificial intelligence
KW  - Computer vision
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Pattern Recognition
KW  - Image Processing and Computer Vision
KW  - Artificial Intelligence (incl. Robotics)
KW  - Algorithm Analysis and Problem Complexity
N1  - 1. Introduction -- 2. Taxonomy -- 3. Representative Feature Coding Algorithms -- 4. Evolution of Feature Coding -- 5. Experimental Study of Feature Coding -- 6. Enhancement via Integrating Spatial Information -- 7. Enhancement via Integrating High Order Coding Information -- 8. Conclusion
N2  - This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) Discuss the applications of feature coding in different visual tasks, analyze the influence of some key factors in feature coding with intensive experimental studies; (5) Provide the suggestions of how to apply different feature coding methods and forecast the potential directions for future work on the topic. It is suitable for students, researchers, practitioners interested in object recognition
UR  - http://dx.doi.org/10.1007/978-3-662-45000-0
ER  -