TL;DR
ASV is a novel stereo vision system that combines a new invariant-based stereo matching algorithm with software optimizations, achieving significant speed and energy efficiency improvements while maintaining high accuracy for applications like AR and autonomous robots.
Contribution
The paper introduces a new stereo matching algorithm, ISM, and software optimizations that together enhance performance and energy efficiency in stereo vision systems.
Findings
5x speedup over existing systems
85% energy savings
0.02% accuracy loss
Abstract
Estimating depth from stereo vision cameras, i.e., "depth from stereo", is critical to emerging intelligent applications deployed in energy- and performance-constrained devices, such as augmented reality headsets and mobile autonomous robots. While existing stereo vision systems make trade-offs between accuracy, performance and energy-efficiency, we describe ASV, an accelerated stereo vision system that simultaneously improves both performance and energy-efficiency while achieving high accuracy. The key to ASV is to exploit unique characteristics inherent to stereo vision, and apply stereo-specific optimizations, both algorithmically and computationally. We make two contributions. Firstly, we propose a new stereo algorithm, invariant-based stereo matching (ISM), that achieves significant speedup while retaining high accuracy. The algorithm combines classic "hand-crafted" stereo…
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