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Existing pedestrian and vehicle detection algorithms use 2D cues of objects, such as pixel values, color, texture, shape information or motion. The use of 3D cues in object detection, on the other hand, is not well studied in the literature. In this paper, we propose an efficient algorithm that detects pedestrian and vehicle using their 3D cues. The proposed algorithm first detects moving objects...
The differences between Principal Component Analysis (PCA) and Independent Component Analysis (ICA) for feature extraction are analyzed theoretically and experimentally, and a mixed PCA/ICA transform is developed for Synthetic Aperture Radar image feature extraction. This method combines the subspace produced by PCA and the subspace generated by ICA to form a mixed subspace to be used to extract features...
The effect of PC (principal component) number upon SAR ATR (synthetic aperture radar automatic target recognition) performance based on PCA (principal component analysis) is analyzed. First, PCA features are extracted with different PC number, and then SVM is used to classify. Experimental results based on MSTAR data sets show that the performance is optimized when the accumulative contribution rate...
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