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|Title:||Integrated approach to three-dimensional motion analysis and object recognition|
|Author(s):||Leung, Mun Keung|
|Doctoral Committee Chair(s):||Huang, Thomas S.|
|Department / Program:||Electrical and Computer Engineering|
|Degree Granting Institution:||University of Illinois at Urbana-Champaign|
|Subject(s):||Engineering, Electronics and Electrical|
|Abstract:||In this thesis, an integrated system for three-dimensional (3-D) motion analysis and object recognition with noisy outdoor stereo images as inputs is presented. The goals are to obtain the 3-D motion description and the identification of the object on the input stereo images. In order to accomplish the desired goals, the system consists of four stages to extract the required information. These four stages are (i) motion estimation, (ii) distinctive feature extraction, (iii) model database, and (iv) object recognition.
The motion estimation is based on 3-D point correspondences which can be derived from matched points on the stereo images. In this stage, we obtain the following: (1) motion parameters, (2) 3-D centroid locations of the object and (3) region of interest (region of the object projected on an image).
With the noisy outdoor stereo images of a vehicle as inputs, there are two features that can be extracted consistently from them. These two features are the region of interest and the wheel pattern of a vehicle. The first feature, region of interest, can be obtained from motion estimation. The second feature, wheel pattern, is extracted in the stage of distinctive feature extraction which involves template matching and the Hough transform. On the other hand, the two corresponding features of a model library can be obtained from its perspective view generated by the model database.
For object recognition, the two features mentioned above are used to describe an object. The description consists of a set of attribute lists which includes (i) region of interest, (ii) number of wheels, (iii) locations of wheels and (iv) size of wheels. By comparing the attribute list set of the image with that of each model library, a confidence measure can be computed. The vehicle on the input images is identified to be one of the model libraries which has the highest value in confidence measure.
The system is applied to sets of stereo image pairs. From the experimental results, the system can successfully provide the 3-D motion description and the identification of the vehicle on all the stereo image pairs.
|Rights Information:||Copyright 1991 Leung, Mun Keung|
|Date Available in IDEALS:||2011-05-07|
|Identifier in Online Catalog:||AAI9136659|
This item appears in the following Collection(s)
Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Electrical and Computer Engineering
Dissertations and Theses in Electrical and Computer Engineering