Embedded Computer Vision

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Kisačanin, Branislav (Επιμελητής έκδοσης), Bhattacharyya, Shuvra S. (Επιμελητής έκδοσης), Chai, Sek (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London, 2009.
• Σειρά: Advances in Pattern Recognition
• Θέματα: Computer science.; Computer graphics.; Image processing.; Pattern recognition.; Computer Science.; Image Processing and Computer Vision.; Pattern Recognition.; Computer Imaging, Vision, Pattern Recognition and Graphics.

 Embedded Computer Vision, exemplified by the migration from powerful workstations to embedded processors in computer vision applications, is a new and emerging field that enables an associated shift in application development and implementation. This comprehensive volume brings together a wealth of experiences from leading researchers in the field of embedded computer vision, from both academic and industrial research centers, and covers a broad range of challenges and trade-offs brought about by this paradigm shift. Part I provides an exposition of basic issues and applications in the area necessary for understanding the present and future work. Part II offers chapters based on the most recent research and results. Finally, the last part looks ahead, providing a sense of what major applications could be expected in the near future, describing challenges in mobile environments, video analytics, and automotive safety applications. Features: • Discusses the latest state-of-the-art techniques in embedded computer vision • Presents a thorough introductory section on hardware and architectures, design methodologies, and video analytics to aid the reader’s understanding through the following chapters • Offers emphasis on tackling important problems for society, safety, security, health, mobility, connectivity, and energy efficiency • Discusses evaluation of trade-offs required to design cost-effective systems for successful products • Explores the advantages of various architectures, development of high-level software frameworks and cost-effective algorithmic alternatives • Examines issues of implementation on fixed-point processors, presented through an example of an automotive safety application • Offers insights from leaders in the field on what future applications will be This book is a welcome collection of stand-alone articles, ideal for researchers, practitioners, and graduate students. It provides historical perspective, the latest research results, and a vision for future developments in the emerging field of embedded computer vision. Supplementary material can be found at http://www.embeddedvisioncentral.com. 

 Hardware Considerations for Embedded Vision Systems -- Design Methodology for Embedded Computer Vision Systems -- We Canwatch It For You Wholesale -- Advances in Embedded Computer Vision -- Using Robust Local Features on DSP-Based Embedded Systems -- Benchmarks of Low-Level Vision Algorithms for DSP, FPGA, and Mobile PC Processors -- SAD-Based Stereo Matching Using FPGAs -- Motion History Histograms for Human Action Recognition -- Embedded Real-Time Surveillance Using Multimodal Mean Background Modeling -- Implementation Considerations for Automotive Vision Systems on a Fixed-Point DSP -- Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications -- Looking Ahead -- Mobile Challenges for Embedded Computer Vision -- Challenges in Video Analytics -- Challenges of Embedded Computer Vision in Automotive Safety Systems.