Intelligent Image and Video Interpretation: Algorithms and Applications

Intelligent Image and Video Interpretation: Algorithms and Applications

Jing Tian (Wuhan University of Science and Technology, China) and Li Chen (Wuhan University of Science and Technology, China)
Indexed In: SCOPUS
Release Date: April, 2013|Copyright: © 2013 |Pages: 277
ISBN13: 9781466639584|ISBN10: 146663958X|EISBN13: 9781466639591|DOI: 10.4018/978-1-4666-3958-4

Description

Due to increasing potential in real-world applications such as visual communications, computer assisted biomedical imaging, and video surveillance, image and video interpretations have become an area of growing interest.

Intelligent Image and Video Interpretation: Algorithms and Applications covers all aspects of image and video analysis from low-level early visions to high-level recognition. This publication highlights how these techniques have become applicable and will prove to be a valuable tool for researchers, professionals, and graduate students working or studying the fields of imaging and video processing.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Algorithms
  • Behavior Analysis
  • Biomedical Imaging
  • Computer Vision & Image Processing
  • Intelligent Technologies
  • Video Surveillance

Reviews and Testimonials

This guide for professionals and researchers working in image and video processing in various disciplines will also be useful as a reference for advanced undergraduate and graduate students. The book covers theoretical and applied aspects of image and video recognition and interpretation and presents real-life applications in areas such as biomedical imaging, visual communications, and video surveillance. Some specific subjects addressed include audio and visual speech recognition, human activity interpretation in image and video sequences, dimension reduction of a local manifold learning algorithm for hyperspectral image classification, and image segmentation based on fuzzy entropy and bee colony algorithms. The editors are affiliated with Wuhan University of Science and Technology.

– Annotation ©2013 Book News Inc. Portland, OR

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Jing Tian received his B.Eng. degree (Electronic and Information Engineering), from School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China, M.Eng. degree (Electronic and Information Engineering), from School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China, Ph.D. degree (Electrical and Electronic Engineering), from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interests include image processing and computer vision.
Li Chen received the PhD degree in computer science and engineering from Nanyang Technological University, Singapore, in 2006. Currently he is an associate professor in the School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China. His research interests include computer vision, visual surveillance, and image processing.

Indices