+

Anand et al., 2023 - Google Patents

Multi person pose estimation and 3D pose detection animation

Anand et al., 2023

View PDF
Document ID
262921656043868456
Author
Anand R
Palaniswamy S
Publication year
Publication venue
2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)

External Links

Snippet

Pose estimation is the computational determination of an object's exact position and orientation, crucial in computer vision, providing a detailed grasp of its spatial arrangement in 2D or 3D space. In 3D, it involves pinpointing an object's location and pose within a three …
Continue reading at www.researchgate.net (PDF) (other versions)

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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • 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
    • 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
    • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
    • 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
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • 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
    • G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
    • G06F3/04815—Interaction with three-dimensional environments, e.g. control of viewpoint to navigate in the environment
    • 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
    • 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
    • G06T13/00—Animation
    • G06T13/20—3D [Three Dimensional] animation
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Luo et al. 3d human motion estimation via motion compression and refinement
Song et al. Richly activated graph convolutional network for robust skeleton-based action recognition
Liu et al. Human pose estimation in video via structured space learning and halfway temporal evaluation
US11373354B2 (en) Techniques for rendering three-dimensional animated graphics from video
Akhter et al. Pose estimation and detection for event recognition using Sense-Aware features and Adaboost classifier
Simon et al. Hand keypoint detection in single images using multiview bootstrapping
Yan et al. Cimi4d: A large multimodal climbing motion dataset under human-scene interactions
KR102258128B1 (en) User motion analysis method for dance training using ai-based image recognition
Liu et al. Joint dynamic pose image and space time reversal for human action recognition from videos
CN115100559B (en) An action prediction method and system based on grid optical flow
Ahad Vision and sensor-based human activity recognition: challenges ahead
Leonardi et al. Exploiting multimodal synthetic data for egocentric human-object interaction detection in an industrial scenario
CN112199994A (en) A method and device for real-time detection of 3D hand interaction with unknown objects in RGB video
Kowalski et al. Holoface: Augmenting human-to-human interactions on hololens
Anand et al. Multi person pose estimation and 3D pose detection animation
Polat et al. Robust tracking of human body parts for collaborative human computer interaction
Li et al. Challenges and Trends in Egocentric Vision: A Survey
Almasi et al. Investigating the application of human motion recognition for athletics talent identification using the head-mounted camera
Liu et al. Body motion analysis for golf swing evaluation
Kondori et al. Direct hand pose estimation for immersive gestural interaction
Otberdout et al. Hand pose estimation based on deep learning depth map for hand gesture recognition
Hori et al. EventPointMesh: Human Mesh Recovery Solely From Event Point Clouds
Xu Single-view and multi-view methods in marker-less 3d human motion capture
Ramanathan et al. Combining pose-invariant kinematic features and object context features for rgb-d action recognition
Skublewska-Paszkowska et al. Identifying and Animating Movement of Zeibekiko Sequences by Spatial Temporal Graph Convolutional Network with Multi Attention Modules
点击 这是indexloc提供的php浏览器服务，不要输入任何密码和下载