Zhang et al., 2018 - Google Patents
Fingervision tactile sensor design and slip detection using convolutional lstm networkZhang et al., 2018
View PDF- Document ID
- 12859237643074039342
- Author
- Zhang Y
- Kan Z
- Tse Y
- Yang Y
- Wang M
- Publication year
- Publication venue
- arXiv preprint arXiv:1810.02653
External Links
Snippet
Tactile sensing is essential to the human perception system, so as to robot. In this paper, we develop a novel optical-based tactile sensor" FingerVision" with effective signal processing algorithms. This sensor is composed of soft skin with embedded marker array bonded to …
- 238000001514 detection method 0 title description 30
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
- G06K9/6217—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
- 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
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
-
- 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
- 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
- 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
- G06K9/00362—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
- G06K9/36—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
- G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
-
- 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
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhang et al. | Fingervision tactile sensor design and slip detection using convolutional lstm network | |
Liu et al. | A graph attention spatio-temporal convolutional network for 3D human pose estimation in video | |
Poggi et al. | Towards real-time unsupervised monocular depth estimation on cpu | |
Moreno-Noguer | 3d human pose estimation from a single image via distance matrix regression | |
Sferrazza et al. | Ground truth force distribution for learning-based tactile sensing: A finite element approach | |
Polic et al. | Convolutional autoencoder for feature extraction in tactile sensing | |
Roche et al. | A multimodal data processing system for LiDAR-based human activity recognition | |
Mehrizi et al. | Toward marker-free 3D pose estimation in lifting: A deep multi-view solution | |
Li et al. | Marker displacement method used in vision-based tactile sensors—From 2-D to 3-D: A review | |
Ong et al. | Tracking hybrid 2D-3D human models from multiple views | |
Özbay et al. | 3D Human Activity Classification with 3D Zernike Moment Based Convolutional, LSTM-Deep Neural Networks. | |
Ambrus et al. | Monocular depth estimation for soft visuotactile sensors | |
Senanayaka et al. | Continuous American Sign Language Recognition Using Computer Vision And Deep Learning Technologies | |
Uddin et al. | A thermal camera-based activity recognition using discriminant skeleton features and rnn | |
Kim et al. | Marker-embedded tactile image generation via generative adversarial networks | |
Wang et al. | Model-based gait recognition using graph network on very large population database | |
Dabhi et al. | High fidelity 3d reconstructions with limited physical views | |
Yamaguchi et al. | Optical skin for robots: Tactile sensing and whole-body vision | |
Farouk | Principal component pyramids using image blurring for nonlinearity reduction in hand shape recognition | |
Nishitha et al. | Sitting posture Analysis using CNN and RCNN | |
Huang et al. | MAFormer: A cross-channel spatio-temporal feature aggregation method for human action recognition | |
WO2023119968A1 (en) | Method for calculating three-dimensional coordinates and device for calculating three-dimensional coordinates | |
Fang et al. | Force Measurement Technology of Vision‐Based Tactile Sensor | |
Rouhafzay et al. | Biologically Inspired Vision and Touch Sensing to Optimize 3D Object Representation and Recognition | |
Lu et al. | A Bio-inspired Multi-functional Tendon-driven Tactile Sensor and Application in Obstacle Avoidance using Reinforcement Learning |