Video emotion positioning method and system
A positioning method and technology of positioning system, applied in the computer field, can solve the problems of small amount of emotional video data, difficulty in classifier training, unsatisfactory classification effect, etc., and achieve the effect of clear boundary
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Embodiment 1
[0056]This embodiment provides a video emotion positioning method, which belongs to the field of computer technology and is applicable to various video emotion positioning business scenarios such as video retrieval, monitoring analysis, and advertisement delivery.
[0057] figure 1 A flow chart of a video emotion localization method provided in Embodiment 1, such as figure 1 As shown, the video emotion localization method specifically includes the following steps:
[0058] S1. Perform fragment positioning on the video to be processed, and extract several candidate fragments.
[0059] Step S1 is the preprocessing of the video to be processed, which is used to extract video candidate segments. The video to be processed can be an input video, or a pre-stored video in the database. For the video to be processed, a segment screening algorithm can be used to screen candidate segments.
[0060] Specifically, the video to be processed is positioned into n candidate segments throug...
Embodiment 2
[0106] In order to implement the video emotion localization method in the first embodiment above, this embodiment provides a video emotion localization system.
[0107] figure 2 It is a schematic structural diagram of a video emotion localization system provided by Embodiment 2 of the present invention. Such as figure 2 As shown, the video emotion localization system 100 at least includes:
[0108] Preprocessing module 1: used for segment positioning of the video to be processed, and extracting several candidate segments;
[0109] Feature extraction module 2: used to extract the feature representation of each frame of the candidate segment through the pre-trained first neural network model;
[0110] Classification and sorting module 3: used to perform emotional classification, boundary regression, emotional sorting and integrity classification on candidate segments based on the feature representation of each frame of the candidate segment through the pre-trained second ne...
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