FR3123487B1 - Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo - Google Patents

Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo Download PDF

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Publication number
FR3123487B1
FR3123487B1 FR2105553A FR2105553A FR3123487B1 FR 3123487 B1 FR3123487 B1 FR 3123487B1 FR 2105553 A FR2105553 A FR 2105553A FR 2105553 A FR2105553 A FR 2105553A FR 3123487 B1 FR3123487 B1 FR 3123487B1
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FR3123487A1 (fr
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Yann Frachi
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Ovomind SA
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Ovomind KK
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Priority to FR2105553A priority Critical patent/FR3123487B1/fr
Priority to PCT/IB2022/054882 priority patent/WO2022249081A1/fr
Priority to US18/564,176 priority patent/US12551783B2/en
Priority to EP22728292.8A priority patent/EP4348598A1/fr
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/20—Input arrangements for video game devices
    • A63F13/21—Input arrangements for video game devices characterised by their sensors, purposes or types
    • A63F13/212—Input arrangements for video game devices characterised by their sensors, purposes or types using sensors worn by the player, e.g. for measuring heart beat or leg activity
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/60—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor
    • A63F13/67—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor adaptively or by learning from player actions, e.g. skill level adjustment or by storing successful combat sequences for re-use
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
    • G06V10/811—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data the classifiers operating on different input data, e.g. multi-modal recognition
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional [3D] objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/15—Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/174—Facial expression recognition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
    • G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/63—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for estimating an emotional state
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/005—Language recognition

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biophysics (AREA)
  • Cardiology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Databases & Information Systems (AREA)
  • Acoustics & Sound (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Signal Processing (AREA)
  • Molecular Biology (AREA)
  • Physiology (AREA)
  • Biomedical Technology (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Child & Adolescent Psychology (AREA)
  • Hospice & Palliative Care (AREA)
  • Psychiatry (AREA)
  • Processing Or Creating Images (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
  • Image Analysis (AREA)

Abstract

L’invention présente un procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo comprenant une étape d’étiquetage de séquences dudit jeu par la génération automatique de descripteurs à des séquences temporelles dudit jeu, caractérisé en ce que ladite étape d’étiquetage consiste à appliquer un traitement numérique, au flux audio, par une architecture de réseau neuronal [par exemple convolutif (CNN) (notamment pour l’audio et l’image) et une couche de codage NLP pour la tâche d'identification du langage, pour extraire une première série de descripteurs horodatés et à appliquer un traitement numérique au flux vidéo pour fournir une deuxième série de descripteurs horodatés par une architecture de réseau neuronal pour la tâche de caractérisation des scènes de chaque image dudit flux vidéo [reconnaissance de caractères sur les sous-titres, l’histogramme colorimétrique, et pour fournir une troisième série de descripteurs par un classificateur de composantes graphiques], et la transmission sous forme de M-uplets à un réseau de neuronele procédé comportant en outre un traitement de biosignaux générés par un moyen d’acquisition de l’état émotionnel d’au moins un joueur pour extraire des signaux horodatés valeur Sarousal(t) et valeur Svalence (t) et leur transmission sous forme de N-uplets à un réseau de neurones le procédé comportant en outre le traitement desdits M-uplets correspondant auxdits descripteurs horodatés du premier et du deuxième type et lesdits N-uplets par un réseau de neurones pour fournir au moins un indicateur prédictif de l’état émotionnel induit par un type de séquence audiovisuelle.
FR2105553A 2021-05-27 2021-05-27 Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo Active FR3123487B1 (fr)

Priority Applications (4)

Application Number Priority Date Filing Date Title
FR2105553A FR3123487B1 (fr) 2021-05-27 2021-05-27 Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo
PCT/IB2022/054882 WO2022249081A1 (fr) 2021-05-27 2022-05-25 Procédé pour la prédiction automatique de l'effet émotionnel produit par une séquence de jeu vidéo
US18/564,176 US12551783B2 (en) 2021-05-27 2022-05-25 Method for automatically predicting the emotional effect producted by a video game sequence
EP22728292.8A EP4348598A1 (fr) 2021-05-27 2022-05-25 Procédé pour la prédiction automatique de l'effet émotionnel produit par une séquence de jeu vidéo

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR2105553 2021-05-27
FR2105553A FR3123487B1 (fr) 2021-05-27 2021-05-27 Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo

Publications (2)

Publication Number Publication Date
FR3123487A1 FR3123487A1 (fr) 2022-12-02
FR3123487B1 true FR3123487B1 (fr) 2024-01-19

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FR2105553A Active FR3123487B1 (fr) 2021-05-27 2021-05-27 Procédé pour la prédiction automatique de l’effet émotionnel produit par une séquence de jeu vidéo

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US (1) US12551783B2 (fr)
EP (1) EP4348598A1 (fr)
FR (1) FR3123487B1 (fr)
WO (1) WO2022249081A1 (fr)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116843798B (zh) * 2023-07-03 2024-07-05 支付宝(杭州)信息技术有限公司 动画生成方法、模型训练方法及装置
FR3161846A1 (fr) 2024-05-06 2025-11-07 Ovomind Sa Module photopléthysmographique

Family Cites Families (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10285634B2 (en) * 2015-07-08 2019-05-14 Samsung Electronics Company, Ltd. Emotion evaluation
CN111742560B (zh) 2017-09-29 2022-06-24 华纳兄弟娱乐公司 向用户提供影视内容的方法和装置
KR102649074B1 (ko) * 2018-01-08 2024-03-18 워너 브로스. 엔터테인먼트 인크. 신경 생리학적 상태의 검출을 위한 사회적 상호작용 애플리케이션
US10449461B1 (en) 2018-05-07 2019-10-22 Microsoft Technology Licensing, Llc Contextual in-game element recognition, annotation and interaction based on remote user input
US10818312B2 (en) 2018-12-19 2020-10-27 Disney Enterprises, Inc. Affect-driven dialog generation
US10835823B2 (en) * 2018-12-27 2020-11-17 Electronic Arts Inc. Sensory-based dynamic game-state configuration
US10918948B2 (en) * 2019-03-19 2021-02-16 modl.ai ApS Game bot generation for gaming applications
US10940393B2 (en) * 2019-07-02 2021-03-09 Electronic Arts Inc. Customized models for imitating player gameplay in a video game
FR3100972B1 (fr) 2019-09-20 2021-09-10 Ovomind K K Système de détermination d’une émotion d’un utilisateur
US20220387887A1 (en) * 2020-03-13 2022-12-08 Google Llc Game content choreography based on game context using semantic natural language processing and machine learning
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Also Published As

Publication number Publication date
US12551783B2 (en) 2026-02-17
WO2022249081A1 (fr) 2022-12-01
EP4348598A1 (fr) 2024-04-10
FR3123487A1 (fr) 2022-12-02
US20240245986A1 (en) 2024-07-25

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