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https://www.nexdata.ai/shujutang/static/image/index/datatang_tuxiang_default.webp
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10,000-Hour Multi-Scenario Egocentric Data Egocentric
Embodied AI training
10,000-Hour Egocentric Full-Body Multimodal DatasetPurpose-built for fine-grained embodied AI manipulation training, spanning diverse real-world scenarios with high-definition stereoscopic video, full-body joint poses, and high-density semantic annotations. This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Data size
10,000-Hour Egocentric Full-Body Multimodal Dataset
Data Distribution
Covers residential, retail & office scenarios (kitchen, bedroom, living room, supermarket, office) with diverse real-life tasks: meal prep, cleaning, storage, garment care, merchandising & picking
Data Content
Each sample includes spatiotemporally aligned 4K stereo video, camera calibration params, 76-point full-body pose & step-by-step annotations
Capture Solution
Adopts PICO 4 Ultra head-mounted stereo camera + wrist & ankle IMU motion capture solution
Data Annotation
Supports dense semantic & action-level annotations; all data passes multi-stage quality control reviews
Data Quality
Supports 4096×1536 / 30fps HD video output, tracks 24 torso joints and 52 hand joints, with frame-wise dense annotations and full-process quality control
Sample
Recommended Dataset
116,048 Sets – 3D Hand Pose & Gesture Recognition Dataset
This dataset contains 116,048 sets of 3D handpose data, each set includes hand mask image(RGB, 24-bit), depth image(16-bit), camera intrinsic parameter file(TXT), 3D keypoints file(OBJ), mesh file(OBJ), gesture type file(TXT), keypoints demo image(JPG), and mesh demo image(JPG). The data is collected indoors, with the right hand (no handheld objects), covering both first-person and third-person perspectives, multiple gesture types, finger poses, hand overall rotation poses, individuals and Kinect devices used. This dataset does not include personally identifiable facial information, with hand mask images and depth images aligned. This dataset can be used for tasks such as handpose recognition, hand 3D reconstruction, and hand keypoints detection.
3D hand pose dataset hand keypoints dataset hand gesture recognition RGB-D hand dataset hand mesh dataset AI training hand pose 3D hand reconstruction computer vision hand dataset gesture recognition data
Details Tell Us Your Special Needs
487c1be5-dcb4-4de2-88a1-122b55d0f15f
Specifications
Sample
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