EVW 2014 : The Tenth Embedded Vision Workshop (CVPR 2014)
Call For Papers
The Tenth IEEE Embedded Vision Workshop
June 28, 2014
held in conjunction with IEEE CVPR 2014
Call For Papers
Recent years have witnessed a significant increase in the use of embedded systems for vision.Applications range from accurate, performance-centric systems to high volume, low-cost, light weight and energy efficient consumer devices. Computer vision has been deployed in many applications, for example, in video search and annotation, surveillance, computer-aided surgery, for gesture and body movement detection in video games, to assist drivers in automotive safety and for in-home monitoring of vulnerable persons. Embedded computer vision is part of a growing trend towards developing low-cost “smart sensors” that use local “analytics” to interpret data, passing on relatively high level alerts or summary information via network connectivity. Embedded vision applications are built upon advances in vision algorithms, embedded processing architectures, advanced circuit technologies, and new electronic system design methodologies. They are implemented on embedded processing devices and platforms such as field programmable gate arrays (FPGAs), programmable digital signal processors (DSPs), graphics processing units (GPUs), and various kinds of heterogeneous multi-core devices. They are developed under significant resource constraints of processing, memory, power, size, and communication bandwidth that pose significant challenges to attaining required levels of performance and speed, and frequently exploit the inherent parallelism of the specialized platforms to address these challenges. Given the heterogeneous and specialized nature of these platforms, efficient development methods are an important issue.
The Embedded Vision Workshop (EVW) aims to bring together researchers working on vision problems that share embedded system characteristics. Research papers are solicited in, but not limited to, the following topics:
• Analysis of vision problems specific to embedded systems.
• Analysis of embedded systems problems specific to computer vision.
• Embedded computer vision for robotics
• New trends in programmable processors and their computational models.
• Applications of and algorithms for embedded vision on standard parallelized platforms such as GPUs (PC, embedded and mobile).
• Applications of and algorithms for embedded vision on reconfigurable platforms such as FPGAs.
• Applications of and algorithms for embedded computer vision on programmable platforms DSPs and multicore SoC such as the Cell Processor.
• Applications of embedded computer vision on mobile devices including phones.
• Biologically-inspired vision and embedded systems
• Computer vision applications distributed between embedded devices and servers
• Social networking embedded computer vision applications
• Educational methods for embedded computer vision
• User interface designs and CAD tools for embedded computer vision applications
• Hardware enhancements (lens, imager, processor) that impact computer vision applications
• Software enhancements (OS, middleware, vision libraries, development tools) that impact embedded computer vision application
• Methods for standardization and measurement of computer vision functionality as they impact embedded computer vision
• Performance metrics for evaluating embedded systems performance.
• Hybrid embedded systems combining vision and other sensor modalities
All of the previous Workshops on Embedded (Computer) Vision (ECVW and EVW) were held in conjunction with CVPR, with the exception for the fifth which was held in conjunction with the 2009 ICCV. These events were very successful. Selected papers workshops have been published in two special issues of major journals (EURASIP Journal on Embedded Systems and CVIU) and in a Springer monograph titled Embedded Computer Vision. The Workshop is now renamed Embedded Vision (EVW) to reflect changes in the field.
Paper submission: March 12, 2014
Notification to the authors: April 14, 2014
Camera ready paper: May 6, 2014
Goksel Dedeoglu, Texas Instruments
Fridtjof Stein, Daimler
Stefano Mattoccia, University of Bologna, Italy
Jagadeesh Sankaran, Texas Instruments
Branislav Kisacanin, Interphase
Margrit Gelautz, Vienna University of Technology
Sek Chai, SRI International
Andrew Hunter, University of Lincoln, UK
Ahmed Nabil Belbachir, AIT Austrian Institute of Technology
Abbes Amira, University of the West of Scotland