Feature Coding for Image Representation and Recognition

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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.

Author(s): Yongzhen Huang, Tieniu Tan
Series: SpringerBriefs in Computer Science
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2014

Language: English
Pages: 74
Tags: Pattern Recognition; Image Processing and Computer Vision; Artificial Intelligence (incl. Robotics); Algorithm Analysis and Problem Complexity

Front Matter....Pages i-xiii
Introduction....Pages 1-7
Taxonomy....Pages 9-13
Representative Feature Coding Algorithms....Pages 15-25
Evolution of Feature Coding....Pages 27-35
Experimental Study of Feature Coding....Pages 37-45
Enhancement via Integrating Spatial Information....Pages 47-58
Enhancement via Integrating High Order Coding Information....Pages 59-70
Conclusion....Pages 71-74