Standard DatasetsHand Key Point Skeleton Dataset
The progress of video and photo editing applications relies heavily on high-quality datasets for machine learning models training. Our carefully selected datasets play a crucial role in enhancing the abilities of such applications, by offering accurate segmentation and recognition of different elements within images and videos.
The "Hand Key Point Skeleton Dataset" is designed for applications in visual entertainment and augmented/virtual reality (AR/VR), featuring a collection of indoor-collected images with a high resolution of 3024 x 4032 pixels. This dataset focuses on labeling 21 key points of the hand skeleton, capturing specific single-handed or two-handed poses such as forming a heart shape, placing a hand on the cheek, stretching, and more.
Sample
Specification
Dataset ID
MD-Image-082
Dataset Name
Hand Key Point Skeleton Dataset
Data Type
ImageVolume
About 10k
Data Collection
Indoor collected images. Resolution is 3024 x 4032.
Annotation
Key Points
Annotation Notes
Collect single-handed or two-handed specific poses, such as heart, cheek, stretch, etc., and label 21 key points of the skeleton
Application Scenarios
Ar/Vr;Visual Entertainment
Data Collections
This dataset includes approximately 10k images, each annotated with 21 key points to map out the hand skeleton in various specific poses. The detailed key point annotations provide invaluable data for developing advanced hand-tracking and gesture-recognition technologies in AR/VR applications, enhancing user interaction in gaming, simulations, and interactive media. Additionally, this dataset supports the creation of realistic hand animations and interactions in visual content, contributing to more immersive and engaging digital experiences.
Quality Assurance
Relevant Open Datasets
To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:
FASSEG Repository [Learn more]
This collection offers datasets for frontal face segmentation (Frontal01 and Frontal02) and a dataset for faces in multiple poses (Multipose01).These datasets can be valuable for training models to perform face segmentation in different orientations and conditions.
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