SYSTEMS AND METHODS FOR OPERATING SEXUAL STIMULATION DEVICE BASED ON REAL-TIME ANALYSIS OF SEXUAL CONTENT

1 . A computer-implemented method, comprising:

facilitating, by a server system, a communication between at least one user device and a sexual stimulation device associated with a user via an application equipped in the at least one user device of the user;

performing, by the server system, selection of one or more target video frames of a video representing sexual content being displayed in the at least one user device, wherein the one or more target video frames are selected based at least on performing a real-time analysis of the sexual content in the video;

extracting, by the server system, at least one feature from the one or more target video frames of the video based at least on one or more artificial intelligence (AI) models, the at least one feature comprising a visual feature;

generating, by the server system, a control signal comprising parameters corresponding to the at least one feature being extracted from the one or more target video frames of the video, wherein the parameters of the control signal are determined based at least on quantifying the at least one feature with predefined weights; and

transmitting, by the server system, the control signal in real time to the at least one user device associated with the user for operating the sexual stimulation device to provide sexual stimulation to the user corresponding to the sexual content being displayed in the video.

2 . The computer-implemented method as claimed in claim 1 , wherein the at least feature further comprises an acoustic feature, and wherein extracting the acoustic feature further comprises:

obtaining, by the server system, audio information from the one or more target video frames comprising the sexual content;

extracting, by the server system, one or more acoustic feature parameters from the audio information, the one or more acoustic feature parameters comprising acoustic category, decibel, tone, periodicity, and semantics; and

determining, by the server system, the parameters for the control signal corresponding to the acoustic features, wherein the parameters of the control signal corresponding to the acoustic features comprise at least one of a type of sexual stimulation device, amplitude, and frequency.

3 . The computer-implemented method as claimed in claim 2 , wherein determining the parameters for the control signal further comprises determining at least one of: the type of sexual stimulation device, and an update value for the amplitude and frequency based on performing a comparison of the one or more acoustic feature parameters with one or more preset values defined for at least the type of sexual stimulation device, amplitude and frequency.

4 . The computer-implemented method as claimed in claim 1 , further comprising:

determining, by the server system, a first set of visual features corresponding to erotic factor in the video; and

performing, by the server system, selection of video frames comprising the first set of visual features in the video as the one or more target video frames,

wherein determining the first set of visual features corresponding to erotic factor in the video and performing selection of the one or more target video frames in the video are based at least on the one or more artificial intelligence (AI) models implementing deep learning technique.

5 . The computer-implemented method as claimed in claim 4 , further comprising:

determining, by the server system, a second set of visual features corresponding to motion information of at least characters of the sexual content in the one or more target video frames of the video based at least on the one or more artificial intelligence (AI) models implementing a cyclic neural network; and

determining, by the server system, the parameters for the control signal corresponding to at least the first set of visual features and the second set of visual features of the visual feature, wherein the parameters of the control signal corresponding to the visual features comprise at least one of a type of sexual stimulation device, amplitude and frequency.

6 . The computer-implemented method as claimed in claim 5 , further comprising:

receiving, by the server system, the one or more target video frames at a time, wherein the one or more target video frames corresponds to a category of intra-frame;

extracting, by the server system, a difference value between the one or more target video frames at each time based at least on the one or more artificial intelligence (AI) models, wherein extracting the difference value comprises:

obtaining a foreground of each of the one or more target video frames at each time,

identifying at least one image factor in terms of at least color, texture, and line of the foreground, and comparing the one or more target video frames received at each time with respect to the at least one image factor; and

determining, by the server system, the parameters for the control signal corresponding to the difference value between the one or more target video frames at each time, wherein the parameters of the control signal corresponding to the one or more target video frames at each time comprises at least one of an amplitude and frequency.

7 . The computer-implemented method as claimed in claim 5 , further comprising:

identifying, by the server system, the frame type of the one or more video frames of the sexual content in the video, the frame type comprising at least a long shot frame and a close shot frame;

determining, by the server system, the second set of visual features in the one or more video frames of the frame type being at least one of the long shot frame and the close shot frame based at least one or more feature detection techniques associated with the one or more artificial intelligence (AI) models; and

computing, by the server system, a change in position of feature points between consecutive video frames of the sexual content in the video associated with the second set of visual features in the one or more target video frames.

8 . The computer-implemented method as claimed in claim 5 , wherein the type of sexual stimulation device associated with the control signal is determined to be at least one of a female sexual stimulation device and a male sexual stimulation device based on the visual features related to a gender of the characters in the sexual content of the video.

9 . The computer-implemented method as claimed in claim 1 , further comprising:

facilitating, by the server system, a connection with a third party video streaming platform rendering at least one of the video comprising the sexual content on a first user device of the at least one user device associated with the user;

generating, by the server system, the control signal based on real-time analysis of the sexual content of the video rendered in a first user device; and

transmitting, by the server system, the control signal to a second user device of the at least one user device associated with the user for operating the sexual stimulation device to provide sexual stimulation to the user corresponding to the sexual content being displayed in the video.

10 . The computer-implemented method as claimed in claim 9 , further comprising:

facilitating, by the server system, a live stream broadcast of the sexual content created by a content creator in the application equipped in the at least one user device associated with the user;

generating, by the server system, the control signal based on performing a real-time analysis of actions performed by the content creator in the live streaming; and

transmitting, by the server system, the control signal to the at least one user device associated with the user for operating the sexual stimulation device to provide sexual stimulation to the user corresponding to the actions performed in the live streaming by the content creator.

11 . The computer-implemented method as claimed in claim 1 , wherein the one or more artificial intelligence (AI) models are trained with a training data, the training data comprising at least sexual content data, control signals data, audio data corresponding to the sexual content and feature points.

12 . The computer-implemented method as claimed in claim 1 , further comprising:

predicting, by the server system, subsequent set of target video frames based at least on the one or more target video frames, wherein the subsequent set of target video frames is predicted based on one or more artificial intelligence (AI) models implementing prediction algorithms;

generating, by the server system, the control signal in real-time for a time window corresponding to the subsequent set of target video frames; and

updating, by the server system, a training data based on the control signal associated with the one or more target video frames and the predicted subsequent set of target video frames.

13 . A server system, comprising:

a communication interface;

a memory storing executable instructions; and

a processor operatively coupled with the communication interface and the memory, the processor configured to execute the executable instructions to cause the server system to at least:

facilitate a communication between at least one user device and a sexual stimulation device associated with a user via an application equipped in the at least one user device of the user,

perform selection of one or more target video frames of a video representing sexual content being displayed in the at least one user device, wherein the one or more target video frames is selected based at least on performing a real-time analysis of the sexual content in the video,

extract at least one feature from the one or more target video frames of the video based at least on one or more artificial intelligence (AI) models, the at least one feature comprising an acoustic feature and a visual feature,

generate a control signal comprising parameters corresponding to the at least one feature being extracted from the one or more target video frames of the video, wherein the parameters of the control signal are determined based at least on quantifying the at least one feature with predefined weights, and

transmit the control signal in real time to the at least one user device associated with the user for operating the sexual stimulation device to provide sexual stimulation to the user corresponding to the sexual content being displayed in the video.

14 . The server system as claimed in claim 13 , wherein the server system is further caused to:

obtain audio information from the one or more target video frames comprising the sexual content;

extract one or more acoustic feature parameters from the audio information, the one or more acoustic feature parameters comprising acoustic category, decibel, tone, periodicity, and semantics; and

determine the parameters for the control signal corresponding to the acoustic features, wherein the parameters of the control signal corresponding to the acoustic features comprise at least one of a type of sexual stimulation device, amplitude and frequency,

wherein determining the parameters for the control signal further comprises determining the type of sexual stimulation device, an update value for the amplitude and frequency based on performing a comparison of the one or more acoustic feature parameters with one or more preset values defined for at least the type of sexual stimulation device, amplitude and frequency.

15 . The server system as claimed in claim 13 , wherein the server system is further caused to:

determine a first set of visual features corresponding to erotic factor in the video; and

perform selection of video frames comprising the first set of visual features in the video as the one or more target video frames, wherein determining the first set of visual features corresponding to erotic factor in the video and selection of the one or more target video frames in the video are based at least on the one or more artificial intelligence (AI) models implementing deep learning technique.

16 . The server system as claimed in claim 15 , wherein the server system is further caused to:

determine a second set of visual features corresponding to motion information of at least characters of the sexual content in the one or more target video frames of the video based at least on the one or more artificial intelligence (AI) models implementing a cyclic neural network; and

determine the parameters for the control signal corresponding to at least the first set of visual features and the second set of visual features, wherein the parameters of the control signal corresponding to the visual features comprise at least one of a type of sexual stimulation device, amplitude and frequency.

17 . The server system as claimed in claim 16 , wherein the server system is further caused to:

receive the one or more target video frames at a time, wherein the one or more target video frames corresponds to a category of intra-frame;

extract a difference value between the one or more target video frames at each time based at least on the one or more artificial intelligence (AI) models, wherein extracting the difference value further comprises:

obtain a foreground of each of the one or more target video frames at each time,

identify at least one image factor in terms of at least color, texture, and line of the foreground, and

compare the one or more target video frames received at each time with respect to the at least one image factor; and

determine the parameters for the control signal corresponding to the difference value between the one or more target video frames at each time, wherein the parameters of the control signal corresponding to the one or more target video frames at each time comprises at least one of an amplitude and frequency.

18 . The server system as claimed in claim 16 , wherein the server system is further caused to:

identify the frame type of the one or more video frames of the sexual content in the video, the frame type comprising at least a long shot frame and a close shot frame;

determine the second set of visual features in the one or more video frames of the frame type being at least one of the long shot frame and the close shot frame based at least one or more feature detection techniques associated with the one or more artificial intelligence (AI) models; and

compute a change in position of feature points between consecutive video frames of the sexual content in the video associated with the second set of visual features in the target video frames.

19 . The server system as claimed in claim 16 , wherein the type of sexual stimulation device associated with the control signal is determined to be at least one of a female sexual stimulation device and a male sexual stimulation device based on the visual features related to a gender of the characters in the sexual content of the video.

20 . The server system as claimed in claim 13 , wherein the one or more artificial intelligence (AI) models are trained with a training data, the training data comprising at least sexual content data, control signals data, audio data corresponding to the sexual content and feature points.