Embedded Vision A Special Issue of the Journal on Computer Vision and Image Understanding

Publication Info

Chief Editor
Avinash C. Kak, Purdue University

Guest Editors
Sek Chai, Sarnoff Corporation
Branislav Kisačanin, Texas Instruments
Nikolaos Bellas, University of Thessaly

Citation Info Volume 114, Issue 11 (2010), pages 1115-1316, November 2010

Articles

• Special issue on embedded vision
  Sek Chai, Branislav Kisačanin, Nikolaos Bellas
• AdaBoost-based face detection for embedded systems
  Ming Yang, James Crenshaw, Bruce Augustine, Russell Mareachen, Ying Wu
• Leveraging cost matrix structure for hardware implementation of stereo disparity computation using dynamic programming
  W. James MacLean, Siraj Sabihuddin, Jamin Islam
• On implementing motion-based Region of Interest detection on multi-core CELL
  Avin Kumar, Baoxin Li
• An efficient, chromatic clustering-based background model for embedded vision platforms
  Brian Valentine, Senyo Apewokin, Linda Wills, Scott Wills
• A real-time versatile roadway path extraction and tracking on an FPGA platform
  Roberto Marzotto, Paul Zoratti, Daniele Bagni, Andrea Colombari, Vittorio Murino
• A fast stereo matching algorithm suitable for embedded real-time systems
  Martin Humenberger, Christian Zinner, Michael Weber, Wilfried Kubinger, Markus Vincze
• Design and implementation of embedded computer vision systems based on particle filters
  Sankalita Saha, Neal K. Bambha, Shuvra S. Bhattacharyya
• Wireless smart camera network for real-time human 3D pose reconstruction
  Zoran Zivkovic
• Light-weight salient foreground detection for embedded smart cameras
  Mauricio Casares, Senem Velipasalar, Alvaro Pinto
• A modified model for the Lobula Giant Movement Detector and its FPGA implementation
  Hongying Meng, Kofi Appiah, Shigang Yue, Andrew Hunter, Mervyn Hobden, Nigel Priestley, Peter Hobden, Cy Pettit
• Multi-view scans alignment for 3D spherical mosaicing in large-scale unstructured environments
  Daniela Craciun, Nicolas Paparoditis, Francis Schmitt
• A parallel histogram-based particle filter for object tracking on SIMD-based smart cameras
  Henry Medeiros, Germán Holguín, Paul J. Shin, Johnny Park
• Highly optimized implementation of OpenCV for the Cell Broadband Engine
  Hiroki Sugano, Ryusuke Miyamoto
• Accelerated hardware video object segmentation: From foreground detection to connected components labelling
  Kofi Appiah, Andrew Hunter, Patrick Dickinson, Hongying Meng
• Performance evaluation of an intelligent video surveillance system – A case study
  Péter L. Venetianer, Hongli Deng
• Accurate hardware-based stereo vision
  Kristian Ambrosch, Wilfried Kubinger

Previous Call for Papers

Aims and Scope

Recent years have witnessed a proliferation of embedded vision systems such as camera phones, automotive vision (automotive safety), video analytics (automated video surveillance), machine vision (quality inspection), vision-assisted robots, and medical imaging devices. Advances in computer vision algorithms, embedded processing architectures, integrated circuit technology, and electronic design methodology are enabling new ways to develop and implement computer vision algorithms, shifting from the traditional workstation to embedded systems.

This special issue is aimed at describing the advances in addressing implementation issues for vision algorithms in embedded systems. A growing community of researchers and practitioners is bridging the gap between the theory and practice, and making design choices through systematic analysis in order to meet embedded system constraints. The focus of this special issue is on research that is related to meeting design constraints such as real-time performance, power consumption, and memory requirements of an embedded camera platform.

Topics relevant to the Special Issue include:

• Analysis of computer vision problems for embedded systems (algorithmic tradeoffs that impact system design)
• Analysis of embedded systems problems for computer vision (real-time performance, power consumption, memory requirements, etc.)
• New system architectures and computation models
• Verification methods for mission-critical systems
• Embedded multiprocessor systems and reconfigurable processors (DSP, FPGA, ASIC, SoC, etc.)
• Hybrid / distributed models and architectures
• Applications of embedded computer vision
• Development tools and methodology

Forward any questions to:(email cviu at computervisioncentral dot com)