Roy et al., 2017 - Google Patents
A novel technique to develop cognitive models for ambiguous image identification using eye trackerRoy et al., 2017
- Document ID
- 13934483560536235049
- Author
- Roy A
- Akhtar M
- Mahadevappa M
- Guha R
- Mukherjee J
- Publication year
- Publication venue
- IEEE Transactions on Affective Computing
External Links
Snippet
Human behavior can be analyzed using Eye tracker. Thus, it is used for revealing the cognitive processes for object identification. Cognitive process is the mental ability for identification of what our eyes see. Vision with 20/20 sometimes may not reveal the purpose …
- 230000001149 cognitive 0 title abstract description 25
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Castellano et al. | Recognising human emotions from body movement and gesture dynamics | |
Bosch et al. | Automatic detection of mind wandering from video in the lab and in the classroom | |
Liu et al. | Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework | |
Dewi et al. | Adjusting eye aspect ratio for strong eye blink detection based on facial landmarks | |
Barca et al. | Unfolding visual lexical decision in time | |
Dittrich | Action categories and the perception of biological motion | |
Roy et al. | A novel technique to develop cognitive models for ambiguous image identification using eye tracker | |
Wang et al. | Automated student engagement monitoring and evaluation during learning in the wild | |
Stewart et al. | Generalizability of Face-Based Mind Wandering Detection across Task Contexts. | |
Lyamin et al. | An approach to biometric identification by using low-frequency eye tracker | |
Tabassum et al. | Non-intrusive identification of student attentiveness and finding their correlation with detectable facial emotions | |
Choi et al. | Robot-assisted ADHD screening in diagnostic process | |
Henni et al. | Feature selection for driving fatigue characterization and detection using visual-and signal-based sensors | |
Arru et al. | Exploiting visual behaviour for autism spectrum disorder identification | |
Thurman et al. | Revisiting the importance of common body motion in human action perception | |
Mock et al. | Predicting ADHD risk from touch interaction data | |
Sadek et al. | Computer Vision Techniques for Autism Symptoms Detection and Recognition: A Survey. | |
Jeong et al. | Eyes on me: Investigating the role and influence of eye-tracking data on user modeling in virtual reality | |
Simeoli et al. | Using machine learning for motion analysis to early detect autism spectrum disorder: A systematic review | |
Kumar et al. | Measuring Non-Typical Emotions for Mental Health: A Survey of Computational Approaches | |
Marusic et al. | Analyzing Data Efficiency and Performance of Machine Learning Algorithms for Assessing Low Back Pain Physical Rehabilitation Exercises | |
US20210256249A1 (en) | Detecting visual attention of children with autism spectrum disorder | |
Lathifah et al. | A Brief Review on Behavior Recognition Based on Key Points of Human Skeleton and Eye Gaze To Prevent Human Error | |
Radha et al. | Ensemble of Behavioral Features for Early Detection of Autism Spectrum Disorder | |
Fakhar et al. | Machine Learning Model to Predict Autism Spectrum Disorder Using Eye Gaze Tracking |