2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Lollypop: Camera-to-Motion-Capture Calibration Verification with a Reference Target
Tianyi Liu, Kevin Harris, Mihika Dave +1
Camera-to-motion-capture (mocap) calibration is essential for using mocap as ground truth in robotics, AR/VR, and other computer vision tasks. However, the calibration can drift af…
Robust Camera-to-Mocap Calibration and Verification for Large-Scale Multi-Camera Data Capture
Tianyi Liu, Christopher Twigg, Patrick Grady +3
Optical motion capture (mocap) systems are widely used for ground-truth capture in AR/VR, SLAM and robotics datasets. These datasets require extrinsic calibration to align mocap co…
SHOW3D: Capturing Scenes of 3D Hands and Objects in the Wild
Patrick Rim, Kevin Harris, Braden Copple +8
Accurate 3D understanding of human hands and objects during manipulation remains a significant challenge for egocentric computer vision. Existing hand-object interaction datasets a…
Glove2Hand: Synthesizing Natural Hand-Object Interaction from Multi-Modal Sensing Gloves
Xinyu Zhang, Ziyi Kou, Chuan Qin +7
Understanding hand-object interaction (HOI) is fundamental to computer vision, robotics, and AR/VR. However, conventional hand videos often lack essential physical information such…