Seeing Eye Drone:A Deep Learning,Vision-based UAV for Assisting the Visually Impaired with Mobility
Seeing Eye Drone assists low-vision persons with environment awareness performing exploration and obstacle detection.The modalities of 3D(stereo)and 2D vision on a drone are compared for this task.Different deep-learning systems are developed including 2D only and 3D+2D networks.Comparisons of retrained networks versus training from scratch are also made and approximately 34,000 samples were collected for training and the resulting SSD CNN architecture is used to determine a user's location and direction of travel.A second network identifies locations of common objects in the scene.The object locations are then compared with the user location/heading and depth data to determine whether they represent obstacles.Obstacles determined to be in the user's region of interest are communicated to the visually-impaired user via Text-to-Speech.Real data from outdoor drone flights that communicate with an Android based application are shown.
Drone Assistive Technology Blind/Low Vision Computer Vision Machine Learning
Lynne Grewe Garrett Stevenson
Computer Science California State Univ.East Bay Hayward,CAUSA
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
283-287
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）