Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Stabilization of an image based tracking system
Download
index.pdf
Date
2015
Author
Şener, Irmak Ece
Metadata
Show full item record
Item Usage Stats
286
views
147
downloads
Cite This
Vision based tracking systems require high resolution images of the targets. In addition, tracking system will try to hold the tracked objects at the center of field of view of the camera to achieve robust and successful tracking. Such systems are usually placed on a platform which is to be controlled by a gimbal. The main job of the gimbal is to get rid of jitters and/or undesirable vibrations of the image platform. In this thesis, such an image platform together with its gimbal, and its controller will be modeled and simulated. The design of the controller will be done to yield the resultant system with the optimum performance. The study will be concluded with hardware-in-the-loop simulation studies and theoretical performances will be compared with the practical system’s performance.
Subject Keywords
Tracking (Engineering).
,
Image processing.
,
Computer vision.
,
Robot vision.
URI
http://etd.lib.metu.edu.tr/upload/12619570/index.pdf
https://hdl.handle.net/11511/25306
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Spatial 3D local descriptors for object recognition in RGB-D images
Loğoğlu, K. Berker; Temizel, Alptekin; Kalkan, Sinan; Department of Information Systems (2016)
Introduction of the affordable but relatively high resolution color and depth synchronized RGB-D sensors, along with the efforts on open-source point-cloud processing tools boosted research in both computer vision and robotics. One of the key areas which have drawn particular attention is object recognition since it is one of the crucial steps for various applications. In this thesis, two spatially enhanced local 3D descriptors are proposed for object recognition tasks: Histograms of Spatial Concentric Surf...
Camera electronics and image enhancement software for infrared detector arrays
Küçükkömürler, Alper; Akın, Tayfun; Department of Environmental Engineering (2012)
This thesis aims to design and develop camera electronics and image enhancement software for infrared detector arrays. It first discusses the camera electronics suitable for infrared detector arrays, then it concentrates on image enhancement software that are implemented including defective pixel correction, contrast enhancement, noise reduction and pseudo coloring. After that, testing and results of the implemented algorithms were presented. Camera electronics and circuit operation frequency are selected c...
Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
LQG/LTR, H-infinity and Mu robust controllers design for line of sight stabilization
Baskın, Mehmet; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2015)
Line of sight stabilization against various disturbances is an essential property of gimbaled vision systems mounted on mobile platforms. As the vision systems are designed to function at longer operating ranges with relatively narrow field of views, the expectations from stabilization loops have increased in recent years. In order to design a good stabilization loop, high gain compensation is required. While satisfying high loop gains for disturbance attenuation, it is also required to satisfy sufficient l...
Visual object detection and tracking using local convolutional context features and recurrent neural networks
Kaya, Emre Can; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2018)
Visual object detection and tracking are two major problems in computer vision which have important real-life application areas. During the last decade, Convolutional Neural Networks (CNNs) have received significant attention and outperformed methods that rely on handcrafted representations in both detection and tracking. On the other hand, Recurrent Neural Networks (RNNs) are commonly preferred for modeling sequential data such as video sequences. A novel convolutional context feature extension is introduc...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
I. E. Şener, “Stabilization of an image based tracking system,” M.S. - Master of Science, Middle East Technical University, 2015.