George et al., 2020 - Google Patents
A robust similarity based deep siamese convolutional neural network for gait recognition across viewsGeorge et al., 2020
- Document ID
- 4219375671744288739
- Author
- George M
- Govindarajan T
- Angamuthu Rajasekaran K
- Bandi S
- Publication year
- Publication venue
- Computational Intelligence
External Links
Snippet
Gait recognition has been considered as the emerging biometric technology for identifying the walking behaviors of humans. The major challenges addressed in this article is significant variation caused by covariate factors such as clothing, carrying conditions and …
- 230000005021 gait 0 title abstract description 256
Classifications
-
- 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
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- 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
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
- G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
-
- 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
- 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
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- 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
- G06K9/00288—Classification, e.g. identification
-
- 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
- G06K9/00369—Recognition of whole body, e.g. static pedestrian or occupant recognition
-
- 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
- G06K9/00275—Holistic features and representations, i.e. based on the facial image taken as a whole
-
- 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
- G06K9/00597—Acquiring or recognising eyes, e.g. iris verification
-
- 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
- G06K9/00006—Acquiring or recognising fingerprints or palmprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Rida et al. | Robust gait recognition: a comprehensive survey | |
| Alotaibi et al. | Improved gait recognition based on specialized deep convolutional neural network | |
| Hassan et al. | Soft biometrics: A survey: Benchmark analysis, open challenges and recommendations | |
| Zhang et al. | Spatial transformer network on skeleton‐based gait recognition | |
| US11961333B2 (en) | Disentangled representations for gait recognition | |
| Ren et al. | Coupled kernel embedding for low-resolution face image recognition | |
| Rajan et al. | Facial expression recognition techniques: a comprehensive survey | |
| Fan et al. | Fusing dynamic deep learned features and handcrafted features for facial expression recognition | |
| Kusakunniran et al. | Gait recognition across various walking speeds using higher order shape configuration based on a differential composition model | |
| Kim et al. | Boosted manifold principal angles for image set-based recognition | |
| Lee et al. | Gait recognition via optimally interpolated deformable contours | |
| CN102938070B (en) | A kind of behavior recognition methods based on action subspace and weight behavior model of cognition | |
| Oh et al. | An analytic Gabor feedforward network for single-sample and pose-invariant face recognition | |
| George et al. | A robust similarity based deep siamese convolutional neural network for gait recognition across views | |
| Liu et al. | Adaptive cascade regression model for robust face alignment | |
| Kusakunniran et al. | Automatic gait recognition using weighted binary pattern on video | |
| Merlin Linda et al. | Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet | |
| Ma et al. | Landmark‐Based Facial Feature Construction and Action Unit Intensity Prediction | |
| Wen et al. | Multi-view gait recognition based on generative adversarial network | |
| Linda et al. | Color-mapped contour gait image for cross-view gait recognition using deep convolutional neural network | |
| Tseng et al. | Human action recognition based on graph-embedded spatio-temporal subspace | |
| Wang et al. | Weighted-fusion feature of MB-LBPUH and HOG for facial expression recognition. | |
| Wang et al. | Gender recognition from visible and thermal infrared facial images | |
| Bekhet et al. | A robust deep learning approach for glasses detection in non‐standard facial images | |
| Fendri et al. | Gait-based person re-identification under covariate factors |