Fast Video Shot Boundary Detection Based on Visual Perception
Yin Gao, Yi Lai, Ying Liu · 2019
Dividing video sequences into shots for video content analysis and video retrieval is very important, so shots are the beginning of these advanced analyses. In this paper, we proposed a new model based on visual perception, which can be expressed as "whole to local", following the concept of human vision. We first browse the video to remove the redundant frames of the video, which can reduce the computational cost. Then, the visual consistency feature of the video is used to construct the consistency function between frames to create pending shots. Finally, the shot boundary detection results are further optimized in conjunction with the motion feature. The new model which contains the inter-frame coherence and optical flow feature for shot boundary detection can shorten the calculation time and detect the shots boundary fast and accurately, without sacrificing detection performance. In terms of evaluation, the precision, recall and F1 value of the model shows good results.