Frankie Lu

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In the recent years, mobile computing platforms are becoming increasingly cheaper and yet more powerful in terms of computational resources. Automobiles provide a suitable environment to deploy such mobile platforms in order to provide low cost driver assistance systems. In this paper, we propose Snap-DAS which is a vision-based driver assistance system(More)
In this paper, we present a distributed embedded vision system that enables surround scene analysis and vehicle threat estimation. The proposed system analyzes the surroundings of the ego-vehicle using four cameras, each connected to a separate embedded processor. Each processor runs a set of optimized vision-based techniques to detect surrounding vehicles,(More)
In the recent years, mobile computing platforms are becoming increasingly cheaper and yet more powerful in terms of computational resources. Automobiles provide a suitable environment to deploy such mobile platforms in order to provide low cost driver assistance systems. In this paper, we propose Snap-DAS which is a vision-based driver assistance system(More)
Vision-based driver assistance systems involve a range of data-intensive operations, which pose challenges in implementing them as robust and real-time systems on resource constrained embedded computing platforms. In order to achieve both high accuracy and real-time performance, the constituent algorithms need to be designed and optimized such that they(More)
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