6533b851fe1ef96bd12a98b7
RESEARCH PRODUCT
Skeletons for parallel image processing: an overview of the SKiPPER project
Dominique GinhacJocelyn Serotsubject
Vehicle tracking system[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer Networks and CommunicationsComputer science02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcomputer.software_genreTheoretical Computer ScienceSoftware portability[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0202 electrical engineering electronic engineering information engineeringcomputer.programming_language020203 distributed computingbusiness.industryProgramming language020207 software engineeringPascal (programming language)Computer Graphics and Computer-Aided DesignSkeleton (computer programming)Parallel image processingData flow diagramHardware and ArchitectureSoftware engineeringbusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftwaredescription
International audience; This paper is a general overview of the SKIPPER project, run at Blaise Pascal University between 1996 and 2002. The main goal of the SKIPPER project was to demonstrate the appli- cability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This project has produced several versions of a full-fledged integrated pa- rallel programming environment (PPE). These PPEs have been used to implement realistic vi- sion applications, such as road following or vehicle tracking for assisted driving, on embedded parallel platforms embarked on semi-autonomous vehicles. All versions of SKIPPER share a common front-end and repertoire of skeletons--presented in previous papers--but differ in the techniques used for implementing skeletons. This paper focuses on these implementation issues, by making a comparative survey, according to a set of four criteria (efficiency, expres- sivity, portability, predictability), of these implementation techniques. It also gives an account of the lessons we have learned, both when dealing with these implementation issues and when using the resulting tools for prototyping vision applications.
year | journal | country | edition | language |
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2002-12-01 |