• This demonstratrion shows a genetic algorithm that tackles the pose estimation problem in the field of computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the 3D structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose of the object as in many of the existing work, our algorithm at the same time searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to two existing algorithms. Our approach outperformed the Lowe’s method and another genetic algorithm by Hati and Sengupta under the presence of point mismatches and outliers. In addition, our algorithm has been used to estimate the pose of a real object, which is applicable to augmented reality applications. For example, the pose obtained was used for inserting artificial objects into an augmented reality movie in this page. In this experiment, the test image sequence was taken by putting a paper box on a rotating turntable. Images were captured using a commercial web camera at a constant time interval. The KLT tracker was used to extract feature points and track them in the image sequence. The known structure, together with point features, were used by our genetic algorithm to track its pose in the image sequence. After the acquisition of the object's pose, three feature points on the paper box in the first image were selected to define a plane for the placement of the virtual object. The synthetic chair was  then placed on this plane using the pose sequence computed by our algorithm. Below is the demonstration video that shows the effects of augmenting the synthetic chair (in blue color) with the real scene.

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