| Summary: | 博士 === 國立中央大學 === 資訊工程研究所 === 96 === Optical flow reveals important correspondence information in the fields of computer vision and pattern recognition. Different from the traditional methods which only use two successive frames, we propose a novel optical flow method by integrating multiple frames. This method has the following characteristics: (1) It is a gradient-based method so that it will not be constrained by the subpixel matching problem, (2) It is a feature-based method so that it can estimate independently of each image point, (3) The reduction of ambiguous matching because of the temporal information included, so that it can also be adopted in the applications based on the dense optical flow field. In the experimental results, we have verified that the
proposed method will produce less ambiguous matching and estimation error. Moreover, the estimation results will be more accurate at good feature points.
To further verify the practicability and effectiveness of the proposed optical flow method, we apply this method to two practical problems in this dissertation. First, in
an intelligent transportation system, the real vehicle speed can be estimated by optical flow at feature points through an image-road mapping. Experimental results show that if optical flow can be successfully and accurately estimated, the speed estimationresults will be close to the real speed. Second, we propose a system to distinguish true faces and face photos based on their motion models. By observing the difference of both models, an LDA-based method and a histogram-based method are proposed to
detect the falsification by using face photo. Experimental results demonstrate that if the multi-frame optical flow method is adopted, the motion difference between true
face and face photo is obvious so that the satisfactory verification rate can be obtained. Finally, concluding remarks of the proposed method are given and the improvement
methods for future works are listed.
|
|---|
