ABSTRACT:

Reconfigurable and heterogeneous systems-on-chip open new opportunities for image processing in different areas such as surveillance, industrial vision, big data analytics, medical imaging or vision for robotics. FPGA-based architectures offer more massive computing capabilities than GPPs and their parallel capabilities create huge opportunities for image processing architectures. However, if the introduction of FPGAs can address some performance issues, it introduces new challenges in terms of programmability, hardware abstraction, efficient matching between HW and SW parts, etc.

The motivation for this special session is to bring together researchers working on Reconfigurable architectures and Computer Vision. It provides a unique opportunity to get to know the work and the people researching in the field, and involve a fruitful exchange of ideas.

Publications for this special session may target smart cameras, embedded vision, and architecture for perception in a robotics context. Key areas include, but are not limited to distributed vision systems, smart intra- or inter-system communication, reconfigurable and heterogeneous computing applied to image processing, as well as new architectures, languages or paradigms for distributed image processing systems.

Demonstrations should focus on the benefits brought by reconfigurability and/or heterogeneity on an image processing system in terms of either speed, load balancing, energy, reliability, approximate computing, fault tolerance, adaptivity, or any other system performance-related property.


ORGANIZERS:

François Berry, Université Clermont-Auvergne (France): francois(_dot_)berry(_at_)uca(_dot_)fr
Maxime Pelcat, INSA Rennes (France): mpelcat(_at_)insa-rennes(_dot_)fr