Surveillance is very essential for the safety of power substation. The detection of whether wearing safety helmets or not for perambulatory workers is the key component of overall intelligent surveillance system in po...
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ISBN:
(纸本)9781538604908
Surveillance is very essential for the safety of power substation. The detection of whether wearing safety helmets or not for perambulatory workers is the key component of overall intelligent surveillance system in power substation. In this paper, a novel and practical safety helmet detection framework based on computer vision, machine learning and image processing is proposed. In order to ascertain motion objects in power substation, the ViBe background modelling algorithm is employed. Moreover, based on the result of motion objects segmentation, real-time human classification framework C4 is applied to locate pedestrian in power substation accurately and quickly. Finally, according to the result of pedestrian detection, the safety helmet wearing detection is implemented using the head location, the color space transformation and the color feature discrimination. Extensive compelling experimental results in power substation illustrate the efficiency and effectiveness of the proposed framework.
With the technologies for machine learning and big data handling new opportunities for classification and prediction tasks have arisen. On the other hand the technology of Automatic Dependent Surveillance-Broadcast (A...
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ISBN:
(纸本)9783736998605
With the technologies for machine learning and big data handling new opportunities for classification and prediction tasks have arisen. On the other hand the technology of Automatic Dependent Surveillance-Broadcast (ADS-B) has become indispensable in aviation in the last ten years. Putting these items together paves the way for new applications for real-time radar surveillance systems. That applies to both the civil environment and the world of military systems. This paper describes the complete processing chain to prepare ADS-B data for machine learning and training, which finally leads to applications that can be applied to real-time systems.
Pedestrian detection plays an important role in unmanned technology. Because of the high efficiency and robustness of the deformable part model, it has been widely applied to the field of pedestrian detection. At pres...
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ISBN:
(纸本)9781538604908
Pedestrian detection plays an important role in unmanned technology. Because of the high efficiency and robustness of the deformable part model, it has been widely applied to the field of pedestrian detection. At present, how to effectively reduce the risk of partial screening of pedestrians has been based on the pattern recognition of pedestrian detection technology in the hot spots. Aiming at this problem, after analyzing the deformable part model deeply, this paper creatively proposes a pedestrian detection method with improved deformable part model. By training the two-pedestrian deformable part model, the method is adopted to reduce the pedestrian detection in the pedestrian detection by matching the image sub-region and matching the matching result. It is shown that the method can improve the detection efficiency while ensuring the detection efficiency, while ensuring the effectiveness of the whole algorithm to meet the real-time requirements of unmanned technology.
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