Abstract
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.
Original language | English (US) |
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Title of host publication | CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems |
Subtitle of host publication | Crossings |
Publisher | Association for Computing Machinery |
Pages | 971-974 |
Number of pages | 4 |
Volume | 2015-April |
ISBN (Electronic) | 9781450331456 |
DOIs | |
State | Published - Apr 18 2015 |
Event | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015 - Seoul, Korea, Republic of Duration: Apr 18 2015 → Apr 23 2015 |
Other
Other | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 4/18/15 → 4/23/15 |