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Video recommending method based on video affective characteristics and conversation models

An emotion feature, video recommendation technology, applied in special data processing applications, instruments, electrical digital data processing and other directions, can solve the problem of ignoring video and other problems, to maintain accuracy and performance, simple and efficient comparison, simple and easy to implement. Effect

Inactive Publication Date: 2013-04-10
BEIHANG UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the fact that the current video recommendation method often ignores the content of the video, and also ignores the user’s need for the video to satisfy their viewing emotion, the present invention proposes a video recommendation method based on video emotional features and conversational models

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  • Video recommending method based on video affective characteristics and conversation models
  • Video recommending method based on video affective characteristics and conversation models
  • Video recommending method based on video affective characteristics and conversation models

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Embodiment Construction

[0041] The present invention will be further described in detail below in conjunction with accompanying drawings and examples.

[0042] The present invention proposes a video recommendation method based on video emotional features and conversational models, which can accurately and efficiently allow users to find videos that meet the user's emotional state and want to watch and websites that contain them, so as to find out content such as videos and web pages similar connections between them.

[0043] The present invention proposes a video recommendation method based on video emotional features and conversational models, and its application scenario is the process of video retrieval and viewing by users on the Internet. The following is a simple example to illustrate the process of video recommendation. Such as figure 1 As shown, the video library contains 12 videos. Assume that initially, the user has not watched any video in the video library. The following operations wi...

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Abstract

The invention provides a video recommending method based on video affective characteristics and conversation models, which is characterized in that: affective characteristics of a video are adopted as the comparison foundation, multiple affective characteristics are extracted from the video and an affiliated sound track to synthesize an attraction-arousal curve diagram (V-A diagram), then the V-Adiagram is homogenized, the homogenized V-A diagram is classified into different identical blocks with a fixed quantity, a color block diagram of each block is determined, a difference of the two color block diagrams on corresponding positions of two pictures is compared to a threshold value to obtain a block difference and a coverage difference, finally the similarity value of the two videos canbe obtained, and a processed result for clustering the similarity value is used as a video recommend result. The method also adopts a conversation model to update the video recommend result during the continuous watching process of a user. Due to the adoption of the method, the video recommend result can more satisfy the current affective status of the user, the clicking rate of the user on the recommended video and the number of the continuously-watched video can be improved.

Description

technical field [0001] The invention belongs to the field of multimedia processing, and relates to video image and sound analysis, emotional feature extraction and similarity comparison, and conversation model establishment, in particular to a video recommendation method based on video emotional features and conversation models. Background technique [0002] The Content Based Video Retrieval (CBVR) method uses the features in the video to obtain the video that the user is interested in, and this field is relatively mature. The analysis and processing of video emotional content is a recently emerging direction in CBVR, but the research on it is increasing. This direction integrates video processing and affective computing, providing a new perspective for video content organization and information mining. The purpose of affective computing is to establish a harmonious human-machine environment by endowing computers with the ability to recognize, understand, express and adapt ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 牛建伟朱沥可
Owner BEIHANG UNIV
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