An Image Processing VLIW Architecture for Real-Time Depth Detection

D. Iorga, R. Nane, Yi Lu, E. V. Dalen, K. Bertels
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引用次数: 4

Abstract

Numerous applications for mobile devices require 3D vision capabilities, which in turn require depth detection since this enables the evaluation of an object's distance, position and shape. Despite the increasing popularity of depth detection algorithms, available solutions need expensive hardware and/or additional ASICs, which are not suitable for low-cost commodity hardware devices. In this paper, we propose a low-cost and low-power embedded solution to provide high speed depth detection. We extend an existing off-the-shelf VLIW image processor and perform algorithmic and architectural optimizations in order to achieve the requested real-time performance speed. Experimental results show that by adding different functional units and adjusting the algorithm to take full advantage of them, a 640x480 image pair with 64 disparities can be processed at 36.75 fps on a single processor instance, which is an improvement of 23% compared to the best state-of-the-art image processor.
用于实时深度检测的图像处理VLIW体系结构
移动设备的许多应用都需要3D视觉功能,这反过来又需要深度检测,因为这可以评估物体的距离、位置和形状。尽管深度检测算法越来越受欢迎,但可用的解决方案需要昂贵的硬件和/或额外的asic,这并不适合低成本的商品硬件设备。在本文中,我们提出了一个低成本和低功耗的嵌入式解决方案,以提供高速深度检测。我们扩展了现有的现成VLIW图像处理器,并进行了算法和架构优化,以达到所要求的实时性能速度。实验结果表明,通过添加不同的功能单元并调整算法以充分利用这些功能单元,在单个处理器实例上可以以36.75 fps的速度处理64个差异的640x480图像对,与目前最先进的图像处理器相比提高了23%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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