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10 novembre 2017

UHA3DS 2018

Catégorie : Conférence internationale

3rd International Workshop on Understanding Human Activities through 3D Sensors (UHA3DS'18)

Lake Tahoe, NV/CA, March 15, 2018



The third edition of the UHA3DS Workshop is hosted by the IEEE Winter Conference on Applications of Computer Vision (WACV 2018) http://wacv18.uccs.us (the previous editions were organized in conjunction with the IEEE International Conference on Automatic Face and Gesture Recognition, FG 2015 and the International Conference on Pattern Recognition ICPR 2016).

The Workshop aims to bring together researchers from computer vision and machine learning communities, working together in a natural synergy and having an interest in using recent computing technologies to understand humans, but also support them. For this purpose, the Workshop intends to gather recent vision-based studies in the fields of static and temporal 3D data capture, modeling and representation, and their applications for social interactions. All aspects of 3D human sensing, such as detecting, tracking, motion and activity understanding will be addressed in the Workshop. The covered topics include 3D pose estimation, human activity analysis, hand gesture analysis, body expression and body language. The Workshop aims to provide an interactive platform for researchers to disseminate their most recent research results, discuss rigorously and systematically potential solutions and challenges, and promote new collaborations among researchers.

The Workshop Call for Papers is available at: http://www-rech.telecom-lille.fr/uha3ds2018/CfP-UHA3DS-2018.pdf 


Papers accepted for publication at the UHA3DS 2018 workshop will appear in the Proceedings of IEEE WACV 2018, published and indexed in IEEE Xplore. Submissions may be up to 8 pages + the references in conference paper format. For review, a complete paper should be submitted using the for_review format and the guidelines provided in the author kit. All reviews are double-blind, so please be careful not to include any identifying information including the authors names or affiliations. All papers should be submitted as PDF files (10 MB maximum).



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