TY - GEN
T1 - Crossing the Road Without Traffic Lights
T2 - 19th International Conference on Image Analysis and Processing, ICIAP 2017
AU - Perry, Adi
AU - Verbin, Dor
AU - Kiryati, Nahum
N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - In the absence of pedestrian crossing lights, finding a safe moment to cross the road is often hazardous and challenging, especially for people with visual impairments. We present a reliable low-cost solution, an Android device attached to a traffic sign or lighting pole near the crossing, indicating whether it is safe to cross the road. The indication can be by sound, display, vibration, and various communication modalities provided by the Android device. The integral system camera is aimed at approaching traffic. Optical flow is computed from the incoming video stream, and projected onto an influx map, automatically acquired during a brief training period. The crossing safety is determined based on a 1-dimensional temporal signal derived from the projection. We implemented the complete system on a Samsung Galaxy K-zoom Android smartphone, and obtained real-time operation. Promising experimental results provide pedestrians with sufficiently early warning of approaching vehicles. The system can serve as a stand-alone safety device, that can be installed where pedestrian crossing lights are ruled out. Requiring no dedicated infrastructure, it can be powered by a solar panel and remotely maintained via the cellular network.
AB - In the absence of pedestrian crossing lights, finding a safe moment to cross the road is often hazardous and challenging, especially for people with visual impairments. We present a reliable low-cost solution, an Android device attached to a traffic sign or lighting pole near the crossing, indicating whether it is safe to cross the road. The indication can be by sound, display, vibration, and various communication modalities provided by the Android device. The integral system camera is aimed at approaching traffic. Optical flow is computed from the incoming video stream, and projected onto an influx map, automatically acquired during a brief training period. The crossing safety is determined based on a 1-dimensional temporal signal derived from the projection. We implemented the complete system on a Samsung Galaxy K-zoom Android smartphone, and obtained real-time operation. Promising experimental results provide pedestrians with sufficiently early warning of approaching vehicles. The system can serve as a stand-alone safety device, that can be installed where pedestrian crossing lights are ruled out. Requiring no dedicated infrastructure, it can be powered by a solar panel and remotely maintained via the cellular network.
KW - Android device
KW - Blind and visually impaired
KW - Optical flow
KW - Pedestrian crossing
KW - Resource-limited computer vision
KW - Traffic analysis
UR - http://www.scopus.com/inward/record.url?scp=85032488359&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-68548-9_49
DO - 10.1007/978-3-319-68548-9_49
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AN - SCOPUS:85032488359
SN - 9783319685472
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 534
EP - 544
BT - Image Analysis and Processing - ICIAP 2017 - 19th International Conference, Proceedings
A2 - Battiato, Sebastiano
A2 - Gallo, Giovanni
A2 - Stanco, Filippo
A2 - Schettini, Raimondo
PB - Springer Verlag
Y2 - 11 September 2017 through 15 September 2017
ER -
