Recent work has identified the lack of space usage rule (SUR) data – e.g. “no smoking”, “no campfires” – as an important limitation of online/mobile maps that presents risks to user safety and the environment. In order to address this limitation, a large-scale means of mapping SURs must be developed. In this paper, we introduce and motivate the problem of mapping space usage rules and take the first steps towards identifying solutions. We show how computer vision can be employed to identify SUR indicators in the environment (e.g. “No Smoking” signs) with reasonable accuracy and describe techniques that can assign each rule to the appropriate geographic feature. We also discuss how our methods can be applied to large repositories of spatially-referenced images (e.g. Google Street View) to generate global-scale datasets of SURs.
Samsonov, Pavel; Tang, Xun; Schoening, Johannes; Kuhn, Werner.
You Can’t Smoke Here: Towards Support for Space Usage Rules in Location-aware Technologies.
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