DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT

Computer vision is a technology intended to replace the visual function in humans with extracting information and features from an image and analyzing the information. In this thesis report presented the process of design and implementation of object tracking system that was built starting with obje...

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Main Author: INDRIATI HADI PUTRI - NIM: 23215369, DEWI
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/26557
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:26557
spelling id-itb.:265572018-03-13T14:10:27ZDESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT INDRIATI HADI PUTRI - NIM: 23215369, DEWI Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/26557 Computer vision is a technology intended to replace the visual function in humans with extracting information and features from an image and analyzing the information. In this thesis report presented the process of design and implementation of object tracking system that was built starting with object recognition in the early stages and then equipped with yaw and pitch system for tracking the position of the object. SIFT algorithm is used as a feature extraction, KNN is used as a classifier and for estimation of homographic changes in objects using RANSAC. In order for objects to be tracked automatically, PID control is used to correct the coordinates obtained when object recognition with center coordinates of the frame. <br /> <br /> The result of this study indicates that the system successfully recognizes objects with keypoints parameter as feature object and different recognition distance on each object. Recognizable objects in this study consisted of drink, towel, medicine and remote with number of keypoints on each object that is 140, 500, 78, 91. The object can be recognize with a distance of 20-80 cm, the furthest distance on a recognizable object is the towel object and the nearest distance is the remote. Object tracking with PID controller successfully implemented on single object displacements and dynamical displacements on moving objects with 11,7% overshoot value of yaw movement and 0% overshoot value of pitch movement and 1,2 seconds risetime. Object position of x and y-axis can be known based on direction move of servo motor yaw and pitch with 150 degree of servo motor reference, object position in right and below of robot if the degree of servo motors less than 150 degrees, in the other hands, object position in left and above of robot if the degree of servo motors more than 150 degrees. <br /> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Computer vision is a technology intended to replace the visual function in humans with extracting information and features from an image and analyzing the information. In this thesis report presented the process of design and implementation of object tracking system that was built starting with object recognition in the early stages and then equipped with yaw and pitch system for tracking the position of the object. SIFT algorithm is used as a feature extraction, KNN is used as a classifier and for estimation of homographic changes in objects using RANSAC. In order for objects to be tracked automatically, PID control is used to correct the coordinates obtained when object recognition with center coordinates of the frame. <br /> <br /> The result of this study indicates that the system successfully recognizes objects with keypoints parameter as feature object and different recognition distance on each object. Recognizable objects in this study consisted of drink, towel, medicine and remote with number of keypoints on each object that is 140, 500, 78, 91. The object can be recognize with a distance of 20-80 cm, the furthest distance on a recognizable object is the towel object and the nearest distance is the remote. Object tracking with PID controller successfully implemented on single object displacements and dynamical displacements on moving objects with 11,7% overshoot value of yaw movement and 0% overshoot value of pitch movement and 1,2 seconds risetime. Object position of x and y-axis can be known based on direction move of servo motor yaw and pitch with 150 degree of servo motor reference, object position in right and below of robot if the degree of servo motors less than 150 degrees, in the other hands, object position in left and above of robot if the degree of servo motors more than 150 degrees. <br />
format Theses
author INDRIATI HADI PUTRI - NIM: 23215369, DEWI
spellingShingle INDRIATI HADI PUTRI - NIM: 23215369, DEWI
DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
author_facet INDRIATI HADI PUTRI - NIM: 23215369, DEWI
author_sort INDRIATI HADI PUTRI - NIM: 23215369, DEWI
title DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
title_short DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
title_full DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
title_fullStr DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
title_full_unstemmed DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION AND TRACKING SYSTEM USING SCALE INVARIANT FEATURE TRANSFORM – K NEAREST NEIGHBORS METHOD WITH PID CONTROL FOR HUMANOID ROBOT
title_sort design and implementation of object recognition and tracking system using scale invariant feature transform ãƒâ€šã‚– k nearest neighbors method with pid control for humanoid robot
url https://digilib.itb.ac.id/gdl/view/26557
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