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Pedestrian detection for surveillance video, which is the basic of person re-identification, aims to capture the pedestrians in the monitors. However, the existing pedestrian detection algorithms still have two issues: (1) The recall and precision are not applicable for complicated scenes; (2) It is limited for processing the high-resolution video in real-time. Therefore, pedestrian detection algorithm...
The Doppler shift effect results in some targets shadows in theirs actual position, and a strong correlation exists between adjacent frames of Video Synthetic Aperture Radar (VideoSAR) imagery. Based on the above rationale, a novel approach to moving targets shadow detection for high-frame-rate VideoSAR imagery sequence is presented. First, a fast preprocessing stage is essential in real applications,...
Illumination condition is one of the most important factors that affect the face recognition performance. Face image illumination quality assessment can predict the face recognition performance under various illumination conditions, which will improve the accuracy and efficiency of the face recognition system. However, the quality scores calculated by the existing methods are weakly correlated with...
Person re-identification is one of the hot topics in computer vision. How to design a robust feature representation to identify pedestrians is a key problem for person re-identification. In this paper, a feature representation based on Multi-Statistics Cascade on Pyramid (MSCP) is proposed for person re-identification. The MSCP feature is composed of deep PCA network feature and hand-crafted features...
The Fine-grained Vehicle recognition is easily affected by small visual changes. The existing recognition methods have less robustness to these conditions (such as illumination, weather changes, etc.) and the accuracy of vehicle recognition in complex environments cannot achieve a satisfying result. In this paper, a high-accuracy fine-grained vehicle recognition method using Convolutional Neural Network...
Vehicle classification plays an important part in Intelligent Transport System (ITS). However, the existing vehicle classification methods are not very robust to various changes such as lighting, weathers, noises, and the classification accuracy has been requiring to be improved. Sparse Representation-based Classifier (SRC) is not sensitive to the shortage and damage of data, the feature selection...
Images/videos captured in low-light conditions often present low luminance and contrast. Although the existing algorithms can improve the subjective perception, color distortion and over-enhancement usually appear, which will disturb the subsequent intelligent analysis. Otherwise, due to high computational complexity, the existing algorithms are difficult to process a high resolution (HR) video (1280×720)...
System uses the voice codec chip analog voice signals TLV320AIC23 A/D conversion, digital audio is passed to the DSP chip TMS320VC5409 sequence processing, DSP algorithms using FFT and CZT transform algorithm the number of sequences of audio spectrum analysis, found that whistle frequency. IIR filter is filtering to produce the frequency of the whistle. Finally the number of sequences then filtered...
In order to effectively restrain inter-area oscillations in power systems, a local measurement based neural excitation controller is proposed to generate global stable signal. This is to replace the global measurement based power system stabilizer (GPSS). The proposed neural controller is constructed by two recurrent neural networks: a recurrent neural identifier (RNID) and a recurrent neural controller...
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