Real-Time Vehicle Trajectory Supervision on the Highway

Chapuis, Roland; Potelle, A.; Brame, J.L.; Chausse, Frédéric

doi:10.1177/027836499501400601

Cited by 28 publications

(19 citation statements)

References 13 publications

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“…The ITERMEM skeleton does not, properly speaking, encapsulate parallel behavior, but is used whenever the iterative nature of the real-time vision algorithms, i.e.,the fact that they do not process single images but continuous streams of images 12 has to be made explicit. A typical situation is when computations on the n th image depend on results computed on the n − 1 th (or n − k th ).…”

Section: Parallel Skeletons For Image Processingmentioning

confidence: 99%

Fast prototyping of parallel-vision applications using functional skeletons

Sérot

Ginhac

Chapuis

et al. 2001

Machine Vision and Applications

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We present a design methodology for real-time vision applications aiming at significantly reducing the design-implement-validate cycle time on dedicated parallel platforms. This methodology is based upon the concept of algorithmic skeletons, i.e., higher order program constructs encapsulating recurring forms of parallel computations and hiding their low-level implementation details. Parallel programs are built by simply selecting and composing instances of skeletons chosen in a predefined basis. A complete parallel programming environment was built to support the presented methodology. It comprises a library of vision-specific skeletons and a chain of tools capable of turning an architectureindependent skeletal specification of an application into an optimized, deadlock-free distributive executive for a wide range of parallel platforms. This skeleton basis was defined after a careful analysis of a large corpus of existing parallel vision applications. The source program is a purely functional specification of the algorithm in which the structure of a parallel application is expressed only as combination of a limited number of skeletons. This specification is compiled down to a parametric process graph, which is subsequently mapped onto the actual physical topology using a third-party CAD software. It can also be executed on any sequential platform to check the correctness of the parallel algorithm. The applicability of the proposed methodology and associated tools has been demonstrated by parallelizing several realistic real-time vision applications both on a multi-processor platform and a network of workstations. It is here illustrated with a complete road-tracking algorithm based upon white-line detection. This experiment showed a dramatic reduction in development times (hence the term fast prototyping), while keeping performances on par with those obtained with the handcrafted parallel version.This paper proposes such a methodology, based upon the concept of parallel skeleton. Skeletons [2,13,39] are highlevel programming constructs encapsulating certain common forms of parallel computations to make them readily available for the application programmer. Since their introduction by Cole in [13], skeletons have motivated a significant body of work, both on theoretical aspects and implementation issues. However, there are relatively few experiences with the approach applied in practice to realistic, large-scale problems. This paper tries to fill this gap by demonstrating the utility of a skeleton-based parallel-programming methodology in the domain of real-time vision applications.It is organized as follows: Section 2 is a general presentation of the so-called skeleton-based parallel-programming methodology and of its application to real-time imageprocessing problems. Section 3 describes a complete parallelprogramming environment (SKIPPER) built upon this approach and covering all the stages of program development, from architecture-independent specification to target code generation. The effectiveness of the pro...

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Section: Parallel Skeletons For Image Processingmentioning

confidence: 99%

Fast prototyping of parallel-vision applications using functional skeletons

Sérot

Ginhac

Chapuis

et al. 2001

Machine Vision and Applications

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“…The basic principle of the visual system is using camera as a navigation tool, to analysis the captured image, to detection and extraction of the lanes to avoid obstacles using stereo vision. France Citroen technology center and Pascal university automation and electronic materials science laboratory in France have cooperation in the development Puegoct system [5]. The main principle is using Gauss filter and filter to calculate lane using gradient derivative of the noise left (or right) edge.…”

Section: Introductionmentioning

confidence: 99%

Road marking abrasion defects detection based on video image processing

2016

ISSPJ

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Pavement marking occupies an important position in the road traffic safety operation. A large number of domestic and foreign research and practice has proved that the effective use and maintenance of road signs and markings reduce traffic accidents and improve the capacity of great significance. The main content of this paper is the design of mobile video image acquisition device to road damage to the road traffic marking defect detection, video image to carry out research on road marking based on wear and breakage from video images. The process is random image acquisition of pavement markings, respectively the image pre-processing, image binarization, marking angle correction, marking extraction and detection. Finally, developing software on marking the wear and damage degree detection based on Matlab software then have an image processing experiments. The results show that the software can accurately detect the road wear and damage situation.

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“…Many studies have been conducted to understand road shapes in the direction of vehicle travel in order to develop visual information processing technology to support autonomous driving and drivers driving vehicles [1][2][3]. A representative study is the study by Waxman and colleagues, which approximates road boundaries by straight lines and reconstructs road shapes from infinitely remote points on the straight lines obtained [4].…”

Section: Introductionmentioning

confidence: 99%

Active contour road model for road tracking and 3D road shape reconstruction

Yagi

Brady

Kawasaki

et al. 2005

Electron Comm Jpn Pt III

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SUMMARYThis paper proposes a road representation model that can detect and track road areas from road scenes photographed by monocular cameras and reconstruct 3D shapes of roads. This model can reconstruct road shapes smoothly and accurately while tracking the road boundaries stably with the parallel property of roads as the active or dynamic contour model constraints. Results of tests on 2500 real road scenes using the model reveal stable road area extraction at a level of 96%.

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Real-Time Vehicle Trajectory Supervision on the Highway

Cited by 28 publications

References 13 publications

Fast prototyping of parallel-vision applications using functional skeletons

Fast prototyping of parallel-vision applications using functional skeletons

Road marking abrasion defects detection based on video image processing

Active contour road model for road tracking and 3D road shape reconstruction

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