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mvpr:thesisprojects [2011/09/29 14:43]
jkamarai
mvpr:thesisprojects [2013/01/30 10:59] (current)
jkamarai [Image Alignment Using Pairwise Matching]
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 ===== Available topics ===== ===== Available topics =====
 +
 +==== Optimal Codebook for Visual Bag of Words ====
 +
 +Visual Bag-of-Words has become one of the key tools for "​google kind of" image based search. In this project you play with the existing code and data and you writen a machine learning algorithm that will iteratively or randomly generate, test and search optimal codebooks for the BoW based image matching. In particular, the codebooks based on linear filters will be considered.
 +
 +  * C/C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Joni Kamarainen
 +  * Please contact the supervisor for more details.
 +
 +==== Image Alignment Using Pairwise Matching ====
 +
 +The main idea of this project is to extend our previous image alignment method using single global seed, to align images pairwise and then build a tree structure which can
 +align each image to any other image via the tree paths. For more details see our BMVC [[http://​www2.it.lut.fi/​mvpr/​data/​Lankinen-bmvc2011.pdf|paper]].
 +
 +  * C/C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Joni Kamarainen
 +  * Please contact the supervisor for more details.
 +
 +==== Model Predictive Visual Servoing ====
 +
 +Visual servoing means the real-time control of robots using vision (images). Model predictive control is a modern control paradigm which uses optimization to choose optimal control decisions by predicting a future evolution of a system and optimizing a control objective for the prediction horizon. Using model predictive control with visual servoing is still in its infancy. In this project you can learn about state-of-the-art of visual control and develop the art even further. ​
 +
 +  * The thesis should review existing literature on visual servoing using model predictive control. An existing robotic system should also be developed further to perform model predictive visual servoing.
 +  * The implementation can be done on MVPR's MELFA robot arm.
 +  * C++ skills required. Matlab skills might be useful in prototyping.
 +  * Supervisor: Prof Ville Kyrki
 +
 +==== Learning Grasp Affordances from Vision ====
 +To grasp an object, a robot needs to know where to place its fingers. The set of good finger placements for a particular object are called grasp affordances. Determining grasp affordances from visual input for unknown objects has gained much interest in robotics research community recently, as this would allow robots to operate in normal household environments. ​
 +  * The thesis should review the recent work on learning grasp affordances from vision and implement an example system using a state-of-the-art approach.
 +  * The implementation can be done on MVPR's MELFA robot arm, Weiss robotics/​Schunk gripper, and Kinect sensor.
 +  * C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Ville Kyrki
 +  * Please contact the supervisor for more details.
 +
 +==== 3D Interest Points from Stereo Images ====
 +
 +Interest points have been the hot topic of computer vision for some time and they are the low level operators for image based search engines.
 +In this project you will step on a cutting-edge topic by developing such interest points further - to be used with a stereo pair images. This means
 +that on the low level you utilise existing interest point detectors, but then you should select only those interest points which match between the
 +left and right view and then add 3D information to them (depth). In this project you learn about stereo imaging and state-of-the-art methods for image-based search.
 +
 +  * C/C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Joni Kamarainen
 +  * Please contact the supervisor for more details.
 +
 +==== What Really is Important in Objects ====
 +
 +This work is based on the hypothesis that there are certain local features which are more important than other. Those features can be found from many natural objects and they appear similarly in objects of a same class (car, face, etc.) In this work you will study such important features and make a detector which automatically finds them. First you will use our existing framework to select points which appear similarly in other examples of the same
 +class and then you devise a detector especially for these points. ​
 +
 +  * C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Joni Kamarainen
 +  * Please contact the supervisor for more details.
 +
 +==== Symbolic Description of 3D Objects ====
 +
 +In this work, you learn some cutting edge technologies. You will learn about local features which are used in modern image based search technologies. Moreover, you will learn about stereo images which can now be produced by off-the-shelf cameras. Your task is to describe a 3D object, captured by a stereo camera, using local symbols - a kind of "3D interest points"​.
 +
 +  * C++ and/or Matlab skills are required.
 +  * Supervisor: Prof Joni Kamarainen
 +  * Please contact the supervisor for more details.
  
 ==== Detection of Things from Images ==== ==== Detection of Things from Images ====