[image 00481] CfP: ACCV 2014

Yasuyuki Matsushita yasumat @ microsoft.com
2014年 2月 7日 (金) 16:31:06 JST



ACCV 2014 (Singapore, Nov 1-5)のCall for Papersを転送させていただきます。

Microsoft Research Asia
URL: http://research.microsoft.com/en-us/people/yasumat/
Email: yasumat @ microsoft.com


Please Accept our Apology for Multiple Posting.


Asian Conference on Computer Vision (ACCV 2014), Singapore Nov 1-5, 2014
URL: www.accv2014.org (http://www.comp.nus.edu.sg/~brown/accv2014/index.html)

Important Dates:
Paper submission deadline:    June 20, 2014 
Workshop proposals deadline: April 15, 2014

The conference proceedings will be published by Springer in the Lecture Notes in Computer Science (LNCS) series. Award-winning papers will be selected to appear in a special issue of Computer Vision and Image Understanding (CVIU).

The 12th Asian Conference on Computer Vision (ACCV 2014) will be held in Singapore on Nov 1-5, 2014. ACCV is a leading biennial international conference focused on computer vision, pattern recognition, and related areas. This highly successful series provides a premier forum for researchers, developers, and practitioners to present and discuss new problems, solutions, and technologies in computer vision and related areas.  ACCV 2014 solicits high-quality original research for publication in its main conference and co-located workshops.

General Chairs:
Michael S. Brown (NUS), Tat-Jen Cham (NTU), Yasuyuki Matsushita (MSRA)

Program Chairs:
Daniel Cremers (TUM), Ian Reid (U. Adelaide), Hideo Saito (Keio U.), Ming-Hsuan Yang (UC Merced)

Topics include (but are not limited to):
  * Motion and Tracking
  * Stereo and Structure from Motion
  * Shape from X
  * Color and Texture
  * Segmentation and Grouping
  * Image-Based Modeling
  * Illumination and Reflectance Modeling
  * Sensors & Early and Biologically-Inspired Vision
  * Computational Photography and Video
  * Object Recognition
  * Object Detection and Categorization
  * Video Analysis and Event Recognition
  * Face and Gesture Analysis
  * Statistical Methods and Learning
  * Performance Evaluation
  * Medical Image Analysis
  * Optimization Methods
  * RGBD and Depth Camera Processing
  * Applications of Computer Vision

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