IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY
Indoor security system like CCTV often failed in ensuring room security from theft. Even massive CCTV installation that cost much could be said still ineffective. This failure caused by two major factor : dead angles and no active processing. In this thesis, a mobile surveillance robot with active c...
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id-itb.:365632019-03-13T14:27:06ZIMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY Hansen Indonesia Final Project surveillance robot, face detection, Viola-Jones , CLAHE, neural network. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/36563 Indoor security system like CCTV often failed in ensuring room security from theft. Even massive CCTV installation that cost much could be said still ineffective. This failure caused by two major factor : dead angles and no active processing. In this thesis, a mobile surveillance robot with active camera processing was designed to navigate autonomously inside any indoor room. The robot built with modified Turtlebot3 Burger robot with additional camera Raspberry Pi Cam, thermal sensor TPA81, and proximity sensor Infrared Sharp. SLAM mapping and autonomous navigation that overcome the dead angle problem was provided by ROS navigation stack. Active face detection was proposed by using custom trained Viola-Jones model, with pre-processing CLAHE for constrast enhancement, finally filtered by post-processing skin detection by using neural network with Hue and Value color input. The result from experiment showed the proposed face detection algorithm by using ROS yielded great accuracy with faster detection time in surveillance robot implementation. text |
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Indonesia |
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Indoor security system like CCTV often failed in ensuring room security from theft. Even massive CCTV installation that cost much could be said still ineffective. This failure caused by two major factor : dead angles and no active processing. In this thesis, a mobile surveillance robot with active camera processing was designed to navigate autonomously inside any indoor room. The robot built with modified Turtlebot3 Burger robot with additional camera Raspberry Pi Cam, thermal sensor TPA81, and proximity sensor Infrared Sharp. SLAM mapping and autonomous navigation that overcome the dead angle problem was provided by ROS navigation stack. Active face detection was proposed by using custom trained Viola-Jones model, with pre-processing CLAHE for constrast enhancement, finally filtered by post-processing skin detection by using neural network with Hue and Value color input. The result from experiment showed the proposed face detection algorithm by using ROS yielded great accuracy with faster detection time in surveillance robot implementation. |
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Final Project |
| author |
Hansen |
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Hansen IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
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Hansen |
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Hansen |
| title |
IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
| title_short |
IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
| title_full |
IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
| title_fullStr |
IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
| title_full_unstemmed |
IMPLEMENTATION OF FACE DETECTION ON ROS BASED SURVEILLANCE ROBOT FOR INDOOR SECURITY |
| title_sort |
implementation of face detection on ros based surveillance robot for indoor security |
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https://digilib.itb.ac.id/gdl/view/36563 |
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