# US 2020/0288206 A1 · System and Method for Segment Relevance Detection for Digital Content > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0288206 A1 - Document ID: US20200288206A1 - Status: Published application - Kind: A1 - Application number: 16/824,407 - Filed: 2020-03-19 - Published: 2020-09-10 - Earliest claimed: 2011-11-07 - Assignees: Monet Networks, Inc. - Applicants: Monet Networks, Inc. - Inventors: Anurag Bist; Ramon Solves Pujol; Eric Leopold Frankel - Web page: https://patentgrep.com/patent/US20200288206A1 ## CPC - G06Q 10/40: Business processes related to social networking or social networking services - G06F 16/7867: {using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings} - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06V 20/49: {Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes} - G06V 40/19: Sensors therefor - H04N 21/23418: {involving operations for analysing video streams, e.g. detecting features or characteristics (television picture signal circuitry for scene change detection H04N5/147; filtering for image enhancement G06T5/00; methods or arrangements for recognising scenes G06V20/00; arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59)} - H04N 21/252: {Processing of multiple end-users' preferences to derive collaborative data} - H04N 21/25891: {being end-user preferences (retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18)} - H04N 21/4223: Cameras (H04N23/00 takes precedence) - H04N 21/44218: {Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV programme (methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45)} - H04N 21/4756: {for rating content, e.g. scoring a recommended movie} - H04N 21/6582: {Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number (arrangements where receivers interact with the broadcast H04H20/38)} - H04N 21/8455: {involving pointers to the content, e.g. pointers to the I-frames of the video stream} - H04N 21/8456: {by decomposing the content in the time domain, e.g. in time segments} - H04N 21/8549: Creating video summaries, e.g. movie trailer {(retrieval in video databases by using presentations in form of a video summary G06F16/739)} - G06V 40/174: {Facial expression recognition} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract In the present embodiment, a system and a method for tagging a content based on individual cues, emotional score or emotional profile is provided, where the content is a video file, a webpage, a mobile application, a product review or product demo video. The method involves authorizing a user to access the content; capturing a user specific data, an application details and a content specific data in response to the content in real-time; analyzing the captured user specific data, the application detail and the content specific data to generate a user emotional profile; and tagging the user emotional profile with the content in a time granular manner. ## Claims ### Claim 1 A system for evaluating media content comprising: a web-based application to stream a media content to a set of participants; a server having a processor, and a facial detection engine, the server is configured to: receive facial expression and emotional engagement of one or more participants of the set of participants in the form of video recordings and processing by the facial detection engine to identify one or more emotions of the set of participants in frame-by-frame manner; receive reactions of one or more participants in the set of participants, in which the reactions are captured by presenting one or more emojis to the second set of participants while the media content is playing, and asking the second set of participants to click emojis at different time of displayed media content to mark corresponding reactions; calculate the emotional valence, the difference of positive emotional values and the negative emotional values at a given time frame, from the facial expression of the set of participants; calculate the reaction valence, the difference of positive reactions and the negative reactions at a given time frame, from the reactions of the set of participants; wherein the server has ability to plot graphical representation of the emotional valence and the reaction valence of the set of participants; wherein the server is configured to identify the one or more time frames in video that has positive peak values and negative peak values in graphical representation of the emotional valence and the reaction valence. ### Claim 2 (depends on 1) The system of claim 1, wherein the positive peak values in the emotional expression graphical representation and the reaction of user represent positive salient scenes. ### Claim 3 (depends on 1) The system of claim 1, wherein the negative peak values in the emotional expression graphical representation and the reaction of user represent negative salient scenes. ### Claim 4 (depends on 2) The system of claim 2, wherein the one or more positive salient scenes represent the most engaging time frame of the media content. ### Claim 5 (depends on 3) The system of claim 3, wherein the negative salient scene represent the least engaging time frame of the media content. ### Claim 6 (depends on 1) The system of claim 1, wherein the server is configured to generate an overall emotional score of the media content using emotional expression of the set of participants that watched the media content and rank one or more media content based on the relevance of emotional score. ### Claim 7 (depends on 1) The system of claim 1, wherein the facial expression data and the reaction data can be captured from the same set of participant or from the different set of participants. ### Claim 8 (depends on 1) The system of claim 1, wherein the emotional expression capture of the set of participants include capturing of a user's gaze at different locations in a given frame of the video content. ### Claim 9 (depends on 8) The system of claim 8, wherein the server generates a heat map displaying the user's gaze focus of the set of participants at different location of a scene of the media content. ### Claim 10 (depends on 1) The system of claim 1, wherein the owner of the media content specify the attributes for the set of participants, which includes, but are not limited to age, demography, ethnicity, gender, region. ### Claim 11 (depends on 1) The system of claim 1, wherein the one or more emotions identified by the facial detection includes but are not limited to Angry, sad, neutral, fear, surprise, joy and disgust. ### Claim 12 (depends on 1) The system of claim 1, wherein the reactions of the set of participants include like, dislike, love, memorable and want. ### Claim 13 A method for evaluating media content comprising: streaming a media content to a first set of participants and a second set of participants; providing a server having a processor, and a facial detection engine, the server is configured to: receive reactions of one or more participants in the set of participants, in which the reactions are captured by presenting one or more emojis to the second set of participants while the media content is playing, and asking the second set of participants to click emojis at different time of displayed media content to mark corresponding reactions; calculate the emotional valence, the difference of positive emotional values and the negative emotional values at a given time frame, from the facial expression of the set of participants; calculate the reaction valence, the difference of positive reactions and the negative reactions at a given time frame, from the reactions of the set of participants; wherein the server has ability to plot graphical representation of the emotional valence and the reaction valence of the set of participants; wherein the server is configured to identify the one or more time frames in video that has positive peak values and negative peak values in graphical representation of the emotional valence and the reaction valence. ### Claim 14 (depends on 13) The method of claim 13, wherein the server is configured to generate an overall emotional score of the media content using emotional expression of the set of participants that watched the media content and rank one or more media content based on the relevance of emotional score. ### Claim 15 (depends on 13) The method of claim 13, wherein the facial expression data and the reaction data can be captured from the same set of participant or from the different set of participants. ### Claim 16 (depends on 13) The method of claim 13, wherein the owner of the media content specify the attributes for the first set of participants and the second set of participants, which includes, but are not limited to age, demography, ethnicity, gender, region. ### Claim 17 (depends on 13) The method of claim 13, wherein the one or more emotions identified by the facial detection includes but are not limited to Angry, sad, neutral, fear, surprise, joy and disgust. ### Claim 18 (depends on 13) The method of claim 13, wherein the reactions of the second set of participants include like, dislike, love, memorable and want. ### Claim 19 (depends on 13) The method of claim 13, wherein the positive peak values in the emotional expression graphical representation and the reaction of user represent positive salient scenes. ### Claim 20 (depends on 13) The method of claim 13, wherein the negative peak values in the emotional expression graphical representation and the reaction of user represent negative salient scenes. ### Claim 21 (depends on 13) The method of claim 13, wherein the one or more positive salient scenes represent the most engaging time frame of the media content. ### Claim 22 (depends on 13) The method of claim 13, wherein the negative salient scene represent the least engaging time frame of the media content. ### Claim 23 (depends on 13) The method of claim 13, wherein the emotional expression capture of the set of participants include capturing of a user's gaze at different locations in a given frame of the video content. ### Claim 24 (depends on 13) The method of claim 13, wherein the server generates a heat map displaying the user's gaze focus of the set of participants at different location of a scene of the media content.