Method for improving VR video interaction efficiencyTechnical Field
The invention relates to the technical field of VR videos, in particular to a method for improving VR video interaction efficiency.
Background
VR is an English abbreviation of Virtual-Reality, chinese means Virtual Reality, and VR video is also called panoramic video, which means that a worker clever artisan can truly record the field environment by using a professional VR photographing function, and then post-process is carried out through a computer, so that the video capable of realizing a three-dimensional space display function is formed.
In the prior art, the interaction efficiency of VR video is low, for single ornamental mode, can only independently select video, reduced the interactive effect of VR video, can not realize that many people are mutual to cause ornamental efficiency low, can not let the sight person feedback interdynamic play the best evaluation, influence the sight experience of follow-up sight person, classification mode singleness does not possess the intelligent recommendation of multiple emphasis element, all kinds of evaluation label sources specialty movie producer in the video simultaneously can not interdynamic ordinary sight person, has reduced interactive scope, influences VR video popularization.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a method for improving the interaction efficiency of VR videos, which can be convenient for interaction to absorb feedback to obtain good works, and can be used for classifying and recommending to obtain videos more in preference, so as to solve the problems that the interaction efficiency of the existing VR videos is low, a single ornamental mode cannot realize multi-person interaction, the classification is single and too fuzzy, and the category which is wanted to be watched cannot be accurately recommended.
In order to achieve the aim, the method for improving the VR video interaction efficiency is realized through the following technical scheme that the method for improving the VR video interaction efficiency is provided with a emphasis classification statistical system, the emphasis classification statistical system comprises a VR interaction video library, a screening module, a video element emphasis screening module, an evaluation statistical module, a malicious screening module and a reward issuing module, the screening module is used for screening basic labels of VR interaction video content, the video element emphasis screening module is used for integrating and screening favorite labels of VR interaction video content recently watched by a user, the evaluation statistical module is used for counting scoring content of the user, the malicious screening module is used for distinguishing whether malicious evaluation exists or not and guaranteeing true and effective scoring, and the reward issuing module is used for encouraging the user to participate in feedback after watching VR interaction video content;
the method comprises the following steps:
Step S1, loading VR interactive video scripts to obtain complete VR interactive video content, and screening VR interactive video content tags on each classification tag page;
Step S2, after the VR interactive video content selected by screening is opened, watching the video, wherein the VR interactive video content realizes real-time scoring through a weighted scoring popup window during watching the video;
Step S3, counting the scoring content of the scoring popup window through an evaluation and statistics module and rewarding;
and S4, extracting tags in the VR interactive video content watched by the user, comparing the data to obtain a preference value, and recommending the VR interactive video content with a high preference value to the home page.
Further, the step S3 further includes a scoring mode, wherein the scoring mode is divided into an advantage scoring mode and a disadvantage scoring mode, the advantage scoring mode is a tenth system, the corresponding rewards are sent out through the rewards issuing module after the advantage scoring, the disadvantage scoring mode is over XX, general XX and slight XX, wherein XX is an element category, the corresponding rewards are sent out through the rewards issuing module after the disadvantage scoring, and the element category comprises heat, evaluation, duration or horror, comedy or love and the like.
Further, the step S3 further includes a prize delivery module, where the prize content of the prize delivery module includes video watching points and evaluation experience, the evaluation experience can promote the video watching points after each evaluation by the user, and the video watching points can obtain the free watching right of the charging VR interactive video content.
Further, the step S4 further includes a video element emphasis screening module, where the video element emphasis screening module substitutes elements of VR interactive video content in the historical viewing record of the user into the first algorithm to obtain preferred element emphasis, and automatically screens out recommended VR interactive video content.
Further, the first algorithm is configured toWhere Ys is the element category, gc is the total number of times of watching, P1 is the element emphasis value, and the element emphasis values are arranged from big to small according to three equal parts to obtain the corresponding element emphasis sequence.
Further, the step S4 further includes element emphasis classification, where the element emphasis classification is that favorite elements are arranged according to a first emphasis element, a second emphasis element and a third emphasis element, and the emphasis proportion is based on VR interactive video content required by screening of the first emphasis element, then screening of the second emphasis element is performed on the screened first emphasis element video, and screening of the third emphasis element is performed on the second element video after screening of the second emphasis element is completed, so as to obtain a three-element mixed video favored by a viewer, and improve the viewing effect accurately.
Further, the step S3 further includes an anti-malicious brushing module, where the anti-malicious brushing module includes a duration statistics unit, a preference bias statistics unit, a fast forward detection unit and a real name authentication unit, the duration statistics unit detects the watching duration of the viewer, when the VR interactive video content is watched and exceeds 80% of the total duration, the precise scoring can be performed, meanwhile, the total duration of the movie at the duration detection position can be used for element emphasis classification, the preference bias statistics unit counts the usual viewing category of the viewer, identifies the usual viewing element category, ensures that no free watching point is brushed, the fast forward detection unit detects whether the viewer fast forwards to the scoring duration, if no fast forward occurs, the free watching point can be obtained, if no fast forward occurs, the reward can be obtained, and the real name authentication unit simultaneously allows the user to fill in and confirm the identity, avoid repeated evaluation, and the evaluation takes effect after the real name authentication.
Further, the step S2 further includes an evaluation classification, wherein the evaluation classification is classified into a rated video and an unevaluated video, the rated video is classified into a popular evaluation and a general evaluation, the popular evaluation is an evaluation exceeding thousands of people, and the general evaluation is an evaluation below thousands of people.
The video viewing method and the video viewing device have the beneficial effects that high-efficiency and accurate element emphasis scoring can be carried out when the VR interactive video content is viewed, the phenomenon that a single video viewing mode is selected to influence the popularization of the VR interactive video content and the understanding speed of people is avoided, and the efficiency of video viewing interaction and the video viewing effect are improved.
According to the invention, through setting the scoring mode and the prize-giving module, the interactive interest can be improved after the film is watched by the film viewer, each work is ensured to be attracted by the prize-giving module, and the scoring mode is used for scoring various elements of the watched VR interactive video content, so that the occupation ratio of each element and the crowd attraction degree are ensured.
According to the invention, by arranging the malicious score-brushing prevention module, the authenticity and the accuracy of a scoring link can be ensured, the normal evaluation of the video watching person is ensured, the existence of malicious score brushing is avoided, and the quality of VR interactive video is ensured.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a system schematic block diagram of the present invention.
In the figure, a classification statistical system is emphasized 1, a VR interactive video library is 2, a screening module is 3, a video element emphasis screening module is 4, an evaluation statistical module is 5, a malicious brushing prevention module is 7, a duration statistical unit is 701, a preference bias statistical unit is 702, a fast forward detection unit is 703, a real name authentication unit is 704, and a prize issuing module is 8.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
Referring to fig. 2, fig. 2 is a schematic block diagram of a system according to the present invention.
The utility model provides an improve interactive efficiency's of VR video system, the system 1 is counted to the focus classification includes VR interactive video storehouse 2, screening module 3, video element focus screening module 4, evaluation statistics module 5, prevents malicious brush and divide module 7 and rewards and issue module 8, screening module 3 is used for screening the basic label of the interactive video content of department VR, video element focus screening module 4 is used for the VR interactive video content label integration screening preference label that the user watched recently, evaluation statistics module 5 is used for counting user's scoring content, prevent malicious brush divide module 7 and be used for discerning whether there is malicious evaluation to guarantee to score true effectively, rewards issue module 8 is used for encouraging the feedback after reinforcing user participated in watching the interactive video content of VR.
The evaluation statistics module 5 comprises a scoring mode, wherein the scoring mode is divided into a merit scoring mode and a disadvantage scoring mode, the merit scoring mode is a tenth system, the corresponding rewards are sent out through the rewards issuing module 8 after the merit scoring, the disadvantage scoring mode is over XX, general XX and slight XX, XX is an element category, and the corresponding rewards are sent out through the rewards issuing module 8 after the disadvantage scoring, wherein the element category comprises heat, evaluation, duration or phobia, comedy or love and the like.
And substituting elements of the VR interactive video content in the historical viewing record of the user into a first algorithm by the video element emphasis screening module 4 to obtain more favorite element emphasis, and automatically screening out recommended VR interactive video content.
The first algorithm is configured asAnd (3) wherein Ys is an element category, gc is the total number of watching, P1 is an element emphasis value, and the element emphasis values are arranged from big to small according to three equal parts to obtain a corresponding element emphasis sequence.
The rewarding content of the rewarding and issuing module 8 comprises video watching points and evaluation experience, the evaluation experience can improve the video watching points after each evaluation of a user, and the video watching points can acquire the free watching right of the charging VR interactive video content.
The evaluation statistics module 5 comprises an anti-malicious brushing module 7, the anti-malicious brushing module 7 is provided with a time length statistics unit 701, a preference deviation statistics unit 702, a fast forward detection unit 703 and a real name authentication unit 704, the watching time length of a video viewer is detected through the time length statistics unit 701, when VR interactive video content is watched and exceeds 80% of the total time length, accurate scoring can be carried out, meanwhile, the total time length of a film at a time length detection position can be used for element side classification, the normal video viewing category of the video viewer is counted through the preference deviation statistics unit 702, the normal video viewing element category is identified, free video viewing points are ensured to be not brushed, whether the video viewer fast forwards to the scoring time length is detected through the fast forward detection unit 703, free video viewing points can be obtained if no fast forward occurs is detected, rewards can not be obtained if fast forward is detected, meanwhile, a user can confirm identity through the real name authentication unit, repeated evaluation is avoided, and evaluation is effective after the real name authentication.
The evaluation statistics module 5 further comprises evaluation classification, wherein the evaluation classification is divided into a rated video and an unevaluated video, the rated video is classified into a popular evaluation and a common evaluation, the popular evaluation is an evaluation exceeding thousands of people, the common evaluation is an evaluation below thousands of people, VR interactive video content in the popular evaluation is conveniently and rapidly obtained by a photo viewer, the precise effect of the evaluation is improved, feedback is finer, and better works are conveniently researched and developed.
Referring to fig. 1, fig. 1 is a flow chart of the method of the present invention.
The method comprises the following steps:
Step S1, loading VR interactive video scripts to obtain complete VR interactive video content, screening VR interactive video content tags on each classification tag page through a screening module, and filling preference tags for viewing;
Step S2, after screening and selecting VR interactive video content, opening the video, realizing real-time scoring of the VR interactive video content through a weighted scoring popup window during video viewing, and selecting a scoring mode, if a plurality of advantages are found during video viewing, selecting an advantage scoring, scoring elements appearing in the video content, if the video terrorism effect is excellent, selecting too terrorism, if the video terrorism effect is insufficient, selecting slight terrorism, and enabling the evaluation item to be fine;
Step S3, counting scoring contents of a scoring popup window through an evaluation statistics module 5, detecting scoring conditions through an anti-malicious scoring module 7, detecting the watching time of a video viewer through a time length statistics unit 70, accurately scoring when VR interactive video contents are watched for more than 80% of the total time length, counting the video viewing categories of the video viewer through a preference bias statistics unit 702, if comedy elements are frequently watched, providing advantage scoring for the views of the comedy, detecting whether the scoring is related to the comedy or not, but depending on whether the element is not strong in side, preventing defects from scoring bad scores and the like, accurately providing the defect directions, ensuring that free video viewing points are not brushed, detecting whether the video viewer fast-forwards to the scoring time length through a fast-forwarding detection unit 703, acquiring free video viewing points if no fast-forwards occur, enabling users to confirm identities through a real-name authentication unit 704, avoiding repeated evaluation, distributing rewards, enabling the content to comprise the promotion of rewards and the evaluation of the video viewing points of the user after the real name authentication, and filling out the free video viewing points after the evaluation of the experience of the video viewing points of the user;
Step S4, extracting tags in VR interactive video contents watched by a user to compare data to obtain a preference value, recommending VR interactive video contents with high preference value to a first page, facilitating other viewers to accurately find the optimal VR interactive video contents in the preference element style, sorting the calculated ratio of element classification in the total number of times of watching by a first algorithm, prioritizing the maximum value as a first side element, classifying the two element categories into a second side element and a third side element, arranging, automatically matching the corresponding VR interactive video contents, recommending the corresponding VR interactive video contents to the user, wherein the comedy element video occupies seven times when the user watches ten times, and the comedy preference value isTerrorist preference values for terrorist elements occurring twice areLove element appears once, and the love preference value isAnd the comedy element videos are sequentially recommended to the uppermost part, and the horror element is the last love element, so that the interaction efficiency is improved.
It should be noted that the foregoing embodiments are merely illustrative embodiments of the present invention, and not restrictive, and the scope of the invention is not limited to the foregoing embodiments, but it should be understood by those skilled in the art that any modification, variation or substitution of some technical features of the foregoing embodiments may be made within the scope of the present invention without departing from the spirit and scope of the technical solutions of the embodiments. Therefore, the protection scope of the invention is subject to the protection scope of the claims.