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- W3015812257 abstract "In current trends, detection and tracking of moving object is significant for video surveillance services. The surveillance concentrates on highly prohibited regions and secured environments. These machine vision systems were widely incorporated in automotive surveillance and traffic monitoring. There are two most key challenges need to be addressed to solve the real-time issues in video surveillance systems are memory requirements to store sequence of information and moving object detection. Hence, the edge detection-based moving object tracking provides better feature vector and higher classification rate for further process. This work discusses the research contribution on edge detection-based depth analysis using TD-WHOG scheme for compression. Also, the conventional standards were failed to exploit better spatio-temporal redundancies, which may not produce considerable coding efficiency for dynamic texture video sequences. So, the prime objective is to suppress the redundancy; dimensionality reduction is the mode of process for increasing the effectiveness." @default.
- W3015812257 created "2020-04-17" @default.
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- W3015812257 date "2020-01-01" @default.
- W3015812257 modified "2023-09-27" @default.
- W3015812257 title "Edge Detection-Based Depth Analysis Using TD-WHOG Scheme" @default.
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- W3015812257 doi "https://doi.org/10.1007/978-981-15-2780-7_44" @default.
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