Rgb-W: When Vision Meets Wireless
2015 IEEE International Conference on Computer Vision (ICCV)(2015)
摘要
Inspired by the recent success of RGB-D cameras, we propose the enrichment of RGB data with an additional "quasi-free" modality, namely, the wireless signal emitted by individuals' cell phones, referred to as RGB-W. The received signal strength acts as a rough proxy for depth and a reliable cue on a person's identity. Although the measured signals are noisy, we demonstrate that the combination of visual and wireless data significantly improves the localization accuracy. We introduce a novel image-driven representation of wireless data which embeds all received signals onto a single image. We then evaluate the ability of this additional data to (i) locate persons within a sparsity-driven framework and to (ii) track individuals with a new confidence measure on the data association problem. Our solution outperforms existing localization methods. It can be applied to the millions of currently installed RGB cameras to better analyze human behavior and offer the next generation of high-accuracy location-based services.
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关键词
RGB-W,RGB-D cameras,quasifree modality,wireless signal,cell phones,received signal strength,wireless data image-driven representation,sparsity-driven framework,data association problem,high-accuracy location-based services
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