TY - GEN
T1 - Smart cane
T2 - 3rd International Conference on Human-Agent Interaction, HAI 2015
AU - Jin, Yongsik
AU - Kim, Jonghong
AU - Kim, Bumhwi
AU - Mallipeddi, Rammohan
AU - Lee, Minho
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/10/21
Y1 - 2015/10/21
N2 - We propose a smart cane with a face recognition system to help the blind in recognizing human faces. This system detects and recognizes faces around them. The result of the detection is informed to the blind person through a vibration pattern. The proposed system was designed to be used in real-time and is equipped with a camera mounted on the glasses, a vibration motor attached to the cane and a mobile computer. The camera attached to the glasses sends image to mobile computer. The mobile computer extracts features from the image and then detects the face using Adaboost. We use the modified census transform (MCT) descriptor for feature extraction. After face detection, the information regarding the detected face image is gathered. We used compressed sensing with L2-norm as a classifier. Cane is equipped with a Bluetooth module and receives a person's information from the mobile computer. The cane generates vibration patterns unique to each person as to inform a blind person about the identity of the detected person using the camera. Hence, the blind people can know the person standing in front of them.
AB - We propose a smart cane with a face recognition system to help the blind in recognizing human faces. This system detects and recognizes faces around them. The result of the detection is informed to the blind person through a vibration pattern. The proposed system was designed to be used in real-time and is equipped with a camera mounted on the glasses, a vibration motor attached to the cane and a mobile computer. The camera attached to the glasses sends image to mobile computer. The mobile computer extracts features from the image and then detects the face using Adaboost. We use the modified census transform (MCT) descriptor for feature extraction. After face detection, the information regarding the detected face image is gathered. We used compressed sensing with L2-norm as a classifier. Cane is equipped with a Bluetooth module and receives a person's information from the mobile computer. The cane generates vibration patterns unique to each person as to inform a blind person about the identity of the detected person using the camera. Hence, the blind people can know the person standing in front of them.
KW - Face detection
KW - Face recognition
KW - Human assistance system
KW - Real-time system
UR - https://www.scopus.com/pages/publications/84962800268
U2 - 10.1145/2814940.2814952
DO - 10.1145/2814940.2814952
M3 - Conference contribution
AN - SCOPUS:84962800268
T3 - HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction
SP - 145
EP - 148
BT - HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction
PB - Association for Computing Machinery, Inc
Y2 - 21 October 2015 through 24 October 2015
ER -