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One of the essential pre-processing steps of semantic video analysis is the video shot boundary detection (SBD). It is the primary step to segment the sequence of video frames into shots. Many SBD systems using supervised learning have been proposed for years; however, the training process still remains its principal limitation. In this paper, a multi-modal visual features-based SBD framework is employed...
Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representation therefore plays an important role in the process where it directly affects the overall performance of the system...
Video shot boundary detection is the process of automatically detecting the meaningful boundary content in video. Most shot boundary categorisation techniques use features extracted from the video frames to highlight the transition points between meaningful scenes. In this paper, a combination of global and local feature descriptors is proposed to represent the temporal characteristic in video. Motivated...
Video shot boundary detection is the process of automatically detecting the meaningful boundary in video data. It becomes an essential pre-processing step to video analysis, summarisation and other content-based retrieval. Video frame feature representation also plays an important role in the process where it directly affects to the performance of the system. Histogram dissimilarity-based with the...
In this paper, we present a reduced-complexity widely-linear (RC-WL) inverse square-root recursive least squares (iQR-RLS) algorithm with the adaptive inverse square-root mechanism, called QR-decomposition for single-carrier frequency-domain equalisation systems. The proposed widely-linear and reduced-complexity widely-linear approaches based on iQR-RLS algorithm are introduced in literature for a...
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