文献类型: 会议论文
第一作者: Ali Isavudeen
作者: Ali Isavudeen 1 ; Nicolas Ngan 1 ; Eva Dokladalova 2 ; Mohamed Akil 2 ;
作者机构: 1.Sagem Defense et Sécurité, Groupe Safran, Argenteuil, France
2.Laboratoire Informatique Gaspard Monge, Equipe A3SI, CNRS-UMLV-ESIEE (UMR 8049), Noisy-le-Grand, France
关键词: Pipelines;Streaming media;Synchronization;Computer architecture;Image resolution;Machine vision;Sensors
会议名称: International Symposium on Circuits and Systems
主办单位:
页码: 2198-2201
摘要: To overcome luminosity problems, modern embedded vision systems often integrate technologically heterogeneous sensors. Also, it has to provide different functionalities such as photo or video mode, image improvement or data fusion, according to the user environment. Therefore, nowadays vision systems should be context-aware and adapt their performance parameters automatically. In this context, we propose a novel auto-adaptive architecture enabling on-the-fly and automatic frame rate and resolution adaptation by a frequency tuning method. This method also intends to reduce power consumption as an alter native to existing power gating method. Performance evaluation on an FPGA implementation demonstrates an interframe adaptation capability with a relatively low area overhead.
分类号: tp-532
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Self-Adaptive Architecture for Multi-Sensor Embedded Vision System
作者:Ali Isavudeen;Eva Dokladalova;Nicolas Ngan;Mohamed Akil
关键词:
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Auto-adaptive multi-sensor architecture
作者:Nicolas Ngan;Eva Dokladalova;Mohamed Akil;Ali Isavudeen
关键词:FPGA;auto-adaptive;multi-sensor;heterogeneous streams;multi-frame rate;multi-resolution;frequency tuning