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ACIVS 2017 : Advanced Concepts for Intelligent Vision SystemsConference Series : Advanced Concepts for Intelligent Vision Systems | |||||||||||||||
Link: http://acivs.org/acivs2017/ | |||||||||||||||
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Call For Papers | |||||||||||||||
Papers must show original and high-quality work, from basic research to pre-industrial application. Topics of interest include, but are not limited to:
Image and Video Processing: preprocessing (scanning, sampling, quantization, …), compressed sensing, filtering, restoration and enhancement, color processing; including applications like multi-camera systems and sensor networks. Multidimensional Image Processing: optical, infrared, radar, sonar, polarimetric, multispectral, hyperspectral and other types of images and videos; including applications like remote sensing and medical applications. Image and Video Analysis: segmentation, computational photography, tracking, pattern analysis, computer vision, early and biologically inspired vision, information geometry, image and video databases, search and retrieval, multimodality, authentication and watermarking; including applications like events supervision, surveillance applications, biometrics and forensics, robotics. Image and Video Coding: coding, quality metrics, image and video protection; including applications like multimedia applications, mobile imaging, augmented reality. Both classical research papers and application papers are welcome. The proceedings of Acivs 2017 will be published by Springer in the Lecture Notes in Computer Science series and are listed in the ISI proceedings index. Best student paper award: Thanks to sponsorship by LNCS, Acivs 2017 will feature a best student paper award with a cash prize. Details will be announced later. Invited speakers: Acivs 2017 will feature the following invited talks: * Antonis Argyros (University of Crete) Tracking humans in interaction with their environment * Daniel Cremers (Technische Universität München) Image based 3D reconstruction and visual slam * Sanja Fidler (University of Toronto) Towards understanding stories in videos |
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