KinDectect: kinect detecting objects

Authors:
Atif Khan;Febin Moideen;Juan Lopez;Wai L. Khoo;Zhigang Zhu
Affiliations:
Department of Computer Science, City College of New York, New York, NY;Department of Computer Science, City College of New York, New York, NY;Department of Computer Science, City College of New York, New York, NY;Department of Computer Science, City College of New York, New York, NY;Department of Computer Science, City College of New York, New York, NY
Venue:
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II
Year:
2012

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Abstract

Detecting humans and objects in images has been a very challenging problem due to variation in illumination, pose, clothing, background and other complexities. Depth information is an important cue when humans recognize objects and other humans. In this work we utilize the depth information that a Kinect sensor - Xtion Pro Live provides to detect humans and obstacles in real time for a blind or visually impaired user. The system runs in two modes. For the first mode, we focus on how to track and/or detect multiple humans and moving objects and transduce the information to the user. For the second mode, we present a novel approach on how to avoid obstacles for safe navigation for a blind or visually-impaired user in an indoor environment. In addition, we present a user study with some blind-folded users to measure the efficiency and robustness of our algorithms and approaches.