# US 11,910,120 B2 · Visual experience modulation based on stroboscopic effect > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,910,120 B2 - Document ID: US11910120B2 - Status: Granted - Kind: B2 - Application number: 17/524,088 - Filed: 2021-11-11 - Published: 2023-05-11 - Granted: 2024-02-20 - Earliest claimed: 2021-11-11 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Diwesh Pandey; Tathagato Bose; Smitkumar Narotambhai Marvaniya; Arun Joseph; Sarbajit K. Rakshit - Web page: https://patentgrep.com/patent/US11910120B2 ## CPC - G11B 27/031: Electronic editing of digitised analogue information signals, e.g. audio or video signals - H04N 5/2625: {for obtaining an image which is composed of images from a temporal image sequence, e.g. for a stroboscopic effect (sequence generated by event triggered capturing H04N7/188)} - G06N 3/045: Combinations of networks - G06N 3/0475: Generative networks - G06N 3/092: Reinforcement learning - G06N 3/094: Adversarial learning - G06N 20/20: Ensemble learning - G06V 20/20: in augmented reality scenes - H04N 5/76: Television signal recording - H04N 9/79: Processing of colour television signals in connection with recording - G11B: INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER (recording measured values in a way that does not require playback through a transducer G01D9/00; recording or playback apparatus using mechanically marked tape, e.g. punched paper tape, or using unit records, e.g. punched or magnetically marked cards G06K; transferring data from one type of record carrier to another G06K1/18; circuits for coupling output of reproducer to radio receiver H04B1/20; gramophone pick-ups or like acoustic electromechanical transducers or circuits therefor H04R) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract An approach for modifying in real-time by removing or reinforcing stroboscopic effect from images associated with a viewing experience is disclosed. The approach includes identifying video clips, detecting environmental parameters and calculating display setting. The approach also analyzes display setting using recommendation from GAN, output displaying setting on an AR display and receiving feedback from user. ## Claims ### Claim 1 A computer-implemented method for modifying in real-time stroboscopic effect, by leveraging machine learning, from one or more video clips, the computer-method comprising: identifying the one or more video clips from a user; receiving IoT (Internet of Things) data from one or more IoT devices; determining an optical data based on the IoT data and the user; determining a stroboscopic effect setting based on the optical data and factors and wherein the factors further comprise of, environmental condition, user medical profile, lighting condition, frequency of light, rotating speed of the object and spatio-temporal object visibility score; executing the stroboscopic effect setting on the one or more video clips; outputting the video clips based on the updated the stroboscopic effecting setting; and receiving one or more feedbacks from the user. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein determining optical data further comprising: collecting the optical data, wherein optical data includes environmental data and user data; and encoding optical data into latent space. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein stroboscopic effect setting further comprises, enabling/disabling stroboscopic effect, enhancing stereoscopic effect and negating stereoscopic effect. ### Claim 4 (depends on 3) The computer-implemented method of claim 3 wherein enabling/disabling stroboscopic effect, enhancing stereoscopic effect or negating stereoscopic effect further comprises, (i) modulating visibility of moving objects and background simultaneously, (ii) augmenting the background and adding transparency, (iii) making the moving object opaque and distinguishing it with respect to the background, (iv) controlling of the stroboscopic effect using light source, (v) making the moving object opaque and distinguishing it with respect to the background, (vi) augmenting the background and adding transparency, (vii) changing the movement of the objects in the video. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein executing stroboscopic effecting setting on the one or more video clips further comprises: generating an augmented video by learning discriminator and generators using various loss functions. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein outputting the video clips based on the updated the stroboscopic effecting setting further comprises: superimposing a GAN (generative adversarial network) generated video as an additional layer with an (AR) augmented reality system. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein receiving feedback from user further comprises: updating model parameters; and fine-tuning the model parameters based on the reward score provided by the user using reinforcement learning. ### Claim 8 A computer program product for modifying in real-time stroboscopic effect from one or more video clips, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions, executable by one or more computer processors, comprising: program instructions to the one or more video clips from a user; program instructions to receive IoT (Internet of Things) data from one or more IoT devices; program instructions to determine an optical data based on the IoT data and the user; program instructions to determine a stroboscopic effect setting based on the optical data and factors and wherein the factors further comprises of, environmental condition, user medical profile, lighting condition, frequency of light, rotating speed of the object and spatio-temporal object visibility score; program instructions to execute stroboscopic effect setting on the one or more video clips; program instructions to output the video clips based on the updated the stroboscopic effecting setting; and program instructions to receive one or more feedbacks from the user. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein program instructions to determine optical data further comprising: program instructions to collect the optical data, wherein optical data includes environmental data and user data; and program instructions to encode optical data into latent space. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein stroboscopic effect setting further comprises, enabling/disabling stroboscopic effect, enhancing stereoscopic effect and negating stereoscopic effect. ### Claim 11 (depends on 10) The computer program product of claim 10, wherein enabling/disabling stroboscopic effect, enhancing stereoscopic effect or negating stereoscopic effect further comprises, (i) modulating visibility of moving objects and background simultaneously, (ii) augmenting the background and adding transparency, (iii) making the moving object opaque and distinguishing it with respect to the background, (iv) controlling of the stroboscopic effect using light source, (v) making the moving object opaque and distinguishing it with respect to the background, (vi) augmenting the background and adding transparency, (vii) changing the movement of the objects in the video. ### Claim 12 (depends on 8) The computer program product of claim 8, wherein program instructions to execute stroboscopic effecting setting on the one or more video clips further comprises: program instructions to generate an augmented video by learning discriminator and generators using various loss functions. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein program instructions to output the video clips based on the updated the stroboscopic effecting setting further comprises: program instructions to superimpose a GAN (generative adversarial network) generated video as an additional layer with an (AR) augmented reality system. ### Claim 14 (depends on 8) The computer program product of claim 8, wherein program instructions to receiving feedback from user further comprises: program instructions to update model parameters; and program instructions to fine-tune the model parameters based on the reward score provided by the user using reinforcement learning. ### Claim 15 A computer system for modifying in real-time stroboscopic effect from one or more video clips, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising: program instructions to the one or more video clips from a user; program instructions to receive IoT (Internet of Things) data from one or more IoT devices; program instructions to determine an optical data based on the IoT data and the user; program instructions to determine a stroboscopic effect setting based on the optical data and factors and wherein the factors further comprises of, environmental condition, user medical profile, lighting condition, frequency of light, rotating speed of the object and spatio-temporal object visibility score; program instructions to execute stroboscopic effect setting on the one or more video clips; program instructions to output the video clips based on the updated the stroboscopic effecting setting; and program instructions to receive one or more feedbacks from the user. ### Claim 16 (depends on 15) The computer system of claim 15, wherein program instructions to determine optical data further comprising: program instructions to collect the optical data, wherein optical data includes environmental data and user data; and program instructions to encode optical data into latent space. ### Claim 17 (depends on 15) The computer system of claim 15, wherein stroboscopic effect setting further comprises, enabling/disabling stroboscopic effect, enhancing stereoscopic effect and negating stereoscopic effect. ### Claim 18 (depends on 17) The computer system of claim 17, wherein enabling/disabling stroboscopic effect, enhancing stereoscopic effect or negating stereoscopic effect further comprises, (i) modulating visibility of moving objects and background simultaneously, (ii) augmenting the background and adding transparency, (iii) making the moving object opaque and distinguishing it with respect to the background, (iv) controlling of the stroboscopic effect using light source, (v) making the moving object opaque and distinguishing it with respect to the background, (vi) augmenting the background and adding transparency, (vii) changing the movement of the objects in the video. ### Claim 19 (depends on 15) The computer system of claim 15, wherein program instructions to execute stroboscopic effecting setting on the one or more video clips further comprises: program instructions to generate an augmented video by learning discriminator and generators using various loss functions. ### Claim 20 (depends on 15) The computer system of claim 15, wherein program instructions to output the video clips based on the updated the stroboscopic effecting setting further comprises: program instructions to superimpose a GAN (generative adversarial network) generated video as an additional layer with an (AR) augmented reality system.