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Camera, and associated with its objects within the field of view, localization could benefit many computer vision fields, such as autonomous driving, robot navigation, and augmented reality (AR). After decades of progress, camera localization, also called camera pose estimation could compute the 6DoF pose of objects for a camera in a given image, with respect to different images in a sequence or formats. Structure-based localization methods have achieved great success when integrated with image matching or with a coordinate regression stage. Absolute and relative pose regression methods using transfer learning can support end-to-end localisation to directly regress a camera pose but achieve a less accurate performance. Despite the rapid development of multiple branches in this area, a comprehensive, in-depth and comparative analysis is lacking to summarise, classify and compare, structure-based and regression-based camera localization methods. Existing surveys either focus on larger SLAM (Simultaneous Localization and Mapping) systems or on only part of the camera localization method, lack detailed comparisons and descriptions of the methods or datasets used, neural network designs such as loss designs, and input formats, etc. In this survey, we first introduce specific application areas and the evaluation metrics for camera localization pose according to different sub-

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Experimental studies on partial discharges (PD) occurred in oil-insulated devices using ultra-high frequency (UHF) sensors to detect PD signals and using wavelet analysis to process the acquired UHF signals are presented, and a threshold selecting method adapting to various noise circumstances when de-noising UHF signals using wavelet transform is proposed in this paper. The threshold method was based on numerical fitting of standard deviations and manual setting thresholds for brush-fire samples from a large scale. Horizontal comparisons between different geometries and vertical comparisons between different intensities of partial discharges in oil were also discussed and the mathematical tool was wavelet analysis. Multi-resolution analysis (MRA) results show the significant differences that can be used to recognize the discharge pattern and to judge the intensity. Particularly attention was given to needle-plate discharge geometry, which was often used by researchers focusing on the mechanism of pre-breakdown phenomena in liquid dielectrics. The results of needle-plate model show good agreement with electronic theory of liquid pre-breakdown mechanism.Index Terms -Partial discharge, wavelet analysis , de-noising, pre-breakdown.

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