Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

Towards Autonomous Depth Perception for Surveillance in Real World Environments

Behara , Gayatri Mayukha
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512398919937727

Abstract Details

2017, Master of Science (M.S.), University of Dayton, Electrical and Computer Engineering.
The widespread emergence of human interactive systems has led to the development of portable 3D depth perception cameras. In this thesis, we aim to expand the functionality of surveillance systems by combining autonomous object recognition along with depth perception to identify an object and its distance from the camera. Specifically, we present an autonomous object detection method using the depth information obtained from the Microsoft Kinect sensor. We use the skeletal joints data obtained from Kinect V2 sensor to determine the hand position of people. The various hand gestures can be classified by training the system with the help of depth information generated by Kinect sensor. Our algorithm then works to detect and identify objects held in the human hand. The proposed system is compact, and the complete video processing can be performed by a low-cost single board computer.
Vamsy Chodavarapu, Dr. (Advisor)
Guru Subramanyam, Dr. (Committee Member)
Vijayan Asari, Dr. (Committee Member)
54 p.
Electrical Engineering

Recommended Citations

Citations

  • Behara , G. M. (2017). Towards Autonomous Depth Perception for Surveillance in Real World Environments [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512398919937727

    APA Style (7th edition)

  • Behara , Gayatri Mayukha . Towards Autonomous Depth Perception for Surveillance in Real World Environments. 2017. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512398919937727.

    MLA Style (8th edition)

  • Behara , Gayatri Mayukha . "Towards Autonomous Depth Perception for Surveillance in Real World Environments." Master's thesis, University of Dayton, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512398919937727

    Chicago Manual of Style (17th edition)

dayton1512398919937727
616
© 2017, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.