Tele-operated search robot for human detection using histogram of oriented objects

Febus Reidj G. Cruz; Glenn O. Avendaño; Cyrel O. Manlises; James Jason G. Avellanosa; Jyacinth Camille F. Abina; Albert M. Masaquel; Michael Lance O. Siapno; Wen-Yaw Chung

doi:10.1117/12.2266932

8 February 2017 Tele-operated search robot for human detection using histogram of oriented objects

Febus Reidj G. Cruz, Glenn O. Avendaño, Cyrel O. Manlises, James Jason G. Avellanosa, Jyacinth Camille F. Abina, Albert M. Masaquel, Michael Lance O. Siapno, Wen-Yaw Chung

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Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102250K (2017) https://doi.org/10.1117/12.2266932
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan

Abstract

Disasters such as typhoons, tornadoes, and earthquakes are inevitable. Aftermaths of these disasters include the missing people. Using robots with human detection capabilities to locate the missing people, can dramatically reduce the harm and risk to those who work in such circumstances. This study aims to: design and build a tele-operated robot; implement in MATLAB an algorithm for the detection of humans; and create a database of human identification based on various positions, angles, light intensity, as well as distances from which humans will be identified. Different light intensities were made by using Photoshop to simulate smoke, dust and water drops conditions. After processing the image, the system can indicate either a human is detected or not detected. Testing with bodies covered was also conducted to test the algorithm’s robustness. Based on the results, the algorithm can detect humans with full body shown. For upright and lying positions, detection can happen from 8 feet to 20 feet. For sitting position, detection can happen from 2 feet to 20 feet with slight variances in results because of different lighting conditions. The distances greater than 20 feet, no humans can be processed or false negatives can occur. For bodies covered, the algorithm can detect humans in cases made under given circumstances. On three positions, humans can be detected from 0 degrees to 180 degrees under normal, with smoke, with dust, and with water droplet conditions. This study was able to design and build a tele-operated robot with MATLAB algorithm that can detect humans with an overall precision of 88.30%, from which a database was created for human identification based on various conditions, where humans will be identified.

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Febus Reidj G. Cruz, Glenn O. Avendaño, Cyrel O. Manlises, James Jason G. Avellanosa, Jyacinth Camille F. Abina, Albert M. Masaquel, Michael Lance O. Siapno, and Wen-Yaw Chung "Tele-operated search robot for human detection using histogram of oriented objects", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250K (8 February 2017); https://doi.org/10.1117/12.2266932

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KEYWORDS

Image processing

MATLAB

Databases

Detection and tracking algorithms

IP cameras

Light sources and illumination

Neodymium

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