碩士 / 國立臺北科技大學 / 電腦與通訊研究所 / 96 / In this paper, we have proposed a modified camera self-calibration approach apply to natural environment for autonomous land vehicle (ALV), based on genetic algorithm (GA).
In this paper, the approach does not need. Firstly, the acquisition image points which are corresponding between the stereo images (left and right), are coplanar. The population created by GA consisting of the camera parameters. Those parameters are used to reproject the 2D image points onto 3D world, then, the points in 3D are regarded the coplanar condition as the objective function, which is to evaluate the parameters. In our research, we adopt the real–coded GA for saving the computation time in encoding and decoding the binary string, but also increasing the precision of the system. There are three ways for the process of selection and reproduction: heuristic crossover, single-point crossover, and combination of the above-mentioned both. The mutation operator applies some random arbitrary number to generate different individuals to avoid the local minimum.
In contrast to the iterative method, GA needs only the reasonable boundary; so that the complex computation kept off since the initial value and the gradient are unnecessary for GA, and the solution is convergence. Some experimental results are also included to demonstrate the applicability of proposed method.
| Identifer | oai:union.ndltd.org:TW/096TIT05652092 |
| Date | January 2008 |
| Creators | Chun-Hao Kao, 高俊豪 |
| Contributors | Rong-Chin Lo, 駱榮欽 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | en_US |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 49 |
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