Elhayek et al., 2018 - Google Patents
Fully automatic multi-person human motion capture for vr applicationsElhayek et al., 2018
- Document ID
- 14907243933152203673
- Author
- Elhayek A
- Kovalenko O
- Murthy P
- Malik J
- Stricker D
- Publication year
- Publication venue
- Virtual Reality and Augmented Reality: 15th EuroVR International Conference, EuroVR 2018, London, UK, October 22–23, 2018, Proceedings 15
External Links
Snippet
Fully automatic tracking of articulated motion in real-time with monocular RGB camera is a challenging problem which is essential for many virtual reality (VR) applications. In this paper, we propose a novel temporally stable solution for this problem which can be directly …
- 210000002356 Skeleton 0 abstract description 84
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- 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
-
- 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
-
- 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
- G06K9/00362—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
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- 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
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
-
- 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
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T13/00—Animation
-
- 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
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Sahu et al. | Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review | |
Rogez et al. | Lcr-net++: Multi-person 2d and 3d pose detection in natural images | |
Pavlakos et al. | Expressive body capture: 3d hands, face, and body from a single image | |
Elhayek et al. | Marconi—convnet-based marker-less motion capture in outdoor and indoor scenes | |
Malleson et al. | Real-time multi-person motion capture from multi-view video and IMUs | |
Weinzaepfel et al. | Dope: Distillation of part experts for whole-body 3d pose estimation in the wild | |
Elhayek et al. | Efficient convnet-based marker-less motion capture in general scenes with a low number of cameras | |
Rhodin et al. | General automatic human shape and motion capture using volumetric contour cues | |
Elhayek et al. | Fully automatic multi-person human motion capture for vr applications | |
Baak et al. | A data-driven approach for real-time full body pose reconstruction from a depth camera | |
Alldieck et al. | Optical flow-based 3d human motion estimation from monocular video | |
EP2843621A1 (en) | Human pose calculation from optical flow data | |
Kemelmacher-Shlizerman et al. | Being john malkovich | |
Rogez et al. | Image-based synthesis for deep 3D human pose estimation | |
Gordon et al. | FLEX: extrinsic parameters-free multi-view 3D human motion reconstruction | |
Puwein et al. | Joint camera pose estimation and 3d human pose estimation in a multi-camera setup | |
Kumar et al. | Human pose estimation using deep learning: review, methodologies, progress and future research directions | |
Romero et al. | FlowCap: 2D human pose from optical flow | |
Cha et al. | Multi-person 3d pose and shape estimation via inverse kinematics and refinement | |
Vo et al. | Spatiotemporal bundle adjustment for dynamic 3d human reconstruction in the wild | |
Ohkawa et al. | Efficient annotation and learning for 3d hand pose estimation: A survey | |
Ugrinovic et al. | Body size and depth disambiguation in multi-person reconstruction from single images | |
Malik et al. | Human action interpretation using convolutional neural network: a survey | |
Mehta et al. | Single-shot multi-person 3d body pose estimation from monocular rgb input | |
Song et al. | VTONShoes: Virtual try-on of shoes in augmented reality on a mobile device |