Meiping Shi

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—Surface reconstruction is one of the main parts of reverse engineering and environment modeling. In this paper a method for reconstruct surface based on Support Vector Machine (SVM) is proposed. In order to overcome the inefficiency of SVM, a feature-preserved nonuniform simplification method is employed to simplify cloud points set. The points set is(More)
This paper proposes a fast and robust algorithm for traffic sign detection and recognition. The algorithm includes two stages: traffic sign detection and recognition. In the first stage, Adaboost algorithm based red pixels model of speed limit sign in the Lab color space is built. Then the model is used to extract area of latent speed limit signs. After(More)
Vision-based road detection is a key component for autonomous vehicle. Existing techniques could be roughly categorized into two categories: off-line training based algorithms and on-line learning based algorithms. While off-line training based algorithms may not adapt well to the new testing scenario, on-line learning based algorithms may not produce(More)
To get sufficient environmental information for a teleoperated unmanned vehicle, a matched image with wide field and high quality image is necessary. Image matching is a key point in image mosaic. And the vast amounts of data and complex calculations make it bottlenecked to get a high speed on mosaicing images. Considering the requirements of real-time(More)
Surface reconstruction based on Support Vector Machine (SVM) is a hot topic in the field of 3-dimension surface construction. But it is difficult to apply this method to cloud points. A reconstruction method based on segmented data is proposed to accelerate SVM regression process from cloud data. First, by partitioning the original sampling data set,(More)
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