23.2 A 1920×1080 30fps 611 mW five-view depth-estimation processor for light-field applications

Hong-Hui Chen, Chao-Tsung Huang, Sih-Sian Wu, Chia-Liang Hung, Tsung-Chuan Ma, Liang-Gee Chen
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引用次数: 13

Abstract

Depth information has become essential in emerging computer vision applications. Although active sensing methods can provide an accurate indoor depth map, they have limited resolution and consume significant power, such as the 2.1W time-of-flight sensor in [1]. In contrast, depth estimation for stereo RGB images can provide high-resolution depth maps, even in outdoor or low-power scenarios. And, the depth accuracy can be increased by using multi-view light-field images. This paper presents an integrated circuit which estimates full HD (1920×1080) depth maps at 30fps and provides a tradeoff between depth accuracy and power consumption based on two-/three-/five-view stereo images. It addresses design challenges with three primary contributions: 1) a stripe buffering scheme which is designed to reduce the DRAM bandwidth induced by multi-view image access; 2) a four-bank interleaving architecture, which boosts computation performance by parallelizing belief-propagation (BP) operations; and, 3) an adaptive view selection unit, which realizes the accuracy-power tradeoff.
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23.2用于光场应用的1920×1080 30fps 611 mW五视图深度估计处理器
在新兴的计算机视觉应用中,深度信息已成为必不可少的。虽然主动传感方法可以提供准确的室内深度图,但它们的分辨率有限,并且消耗大量功率,例如[1]中的2.1W飞行时间传感器。相比之下,立体RGB图像的深度估计可以提供高分辨率的深度图,即使在室外或低功耗场景下也是如此。利用多视点光场图像可以提高深度精度。本文提出了一种集成电路,它可以在30fps下估计全高清(1920×1080)深度图,并在基于二/三/五视图立体图像的深度精度和功耗之间进行权衡。它通过三个主要贡献来解决设计挑战:1)条带缓冲方案,旨在减少多视图图像访问引起的DRAM带宽;2)四行交错架构,通过并行化信念传播(BP)操作来提高计算性能;3)自适应视图选择单元,实现了精度与功率的平衡。
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