Results 11 to 20 of about 930,742 (332)
Human Motion Capture Using a Drone [PDF]
2018 IEEE International Conference on Robotics and Automation (ICRA), 2018 In International Conference on Robotics and Automation (ICRA ...
Zhou, Xiaowei +4 more
openaire +4 more sources
Towards Robust and Accurate Single-View Fast Human Motion Capture
IEEE Access, 2019 This paper proposes a new method for fast human motion capture based on a single RGB-D sensor. By leveraging the human pose detection results for reinitializing the ICP-based sequential human motion tracking algorithm when tracking failure happens, our ...
Tao Yu +4 more
doaj +2 more sources
Real-Time Human Motion Capture Driven by a Wireless Sensor Network
International Journal of Computer Games Technology, 2015 The motion of a real object model is reconstructed through measurements of the position, direction, and angle of moving objects in 3D space in a process called “motion capture.” With the development of inertial sensing technology, motion capture systems ...
Peng-zhan Chen +3 more
doaj +2 more sources
A wearable motion capture device able to detect dynamic motion of human limbs
Nature Communications, 2020 Current wearable motion capture technologies are unable to accurately detect dynamic motion of human limbs due to drift and instability problems. Here, the authors report a wearable motion capture device combining tri-axis velocity sensor and inertial ...
Shiqiang Liu +3 more
doaj +2 more sources
Real-Time Human Motion Capture with Multiple Depth Cameras [PDF]
Canadian Conference on Computer and Robot Vision, 2016 Commonly used human motion capture systems require intrusive attachment of markers that are visually tracked with multiple cameras. In this work we present an efficient and inexpensive solution to markerless motion capture using only a few Kinect sensors.
Little, James J., Shafaei, Alireza
core +2 more sources
Fusing Monocular Images and Sparse IMU Signals for Real-time Human Motion Capture [PDF]
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia, 2023 Either RGB images or inertial signals have been used for the task of motion capture (mocap), but combining them together is a new and interesting topic. We believe that the combination is complementary and able to solve the inherent difficulties of using
Shaohua Pan +7 more
semanticscholar +1 more source
Neural monocular 3D human motion capture with physical awareness [PDF]
ACM Transactions on Graphics, 2021 We present a new trainable system for physically plausible markerless 3D human motion capture, which achieves state-of-the-art results in a broad range of challenging scenarios.
Soshi Shimada +4 more
semanticscholar +1 more source
LiDARCap: Long-range Markerless 3D Human Motion Capture with LiDAR Point Clouds [PDF]
Computer Vision and Pattern Recognition, 2022 Existing motion capture datasets are largely short-range and cannot yet fit the need of long-range applications. We propose LiDARHuman26M, a new human motion capture dataset captured by LiDAR at a much longer range to overcome this limitation.
Jialian Li +8 more
semanticscholar +1 more source
UnrealEgo: A New Dataset for Robust Egocentric 3D Human Motion Capture [PDF]
European Conference on Computer Vision, 2022 We present UnrealEgo, i.e., a new large-scale naturalistic dataset for egocentric 3D human pose estimation. UnrealEgo is based on an advanced concept of eyeglasses equipped with two fisheye cameras that can be used in unconstrained environments.
Hiroyasu Akada +5 more
semanticscholar +1 more source
Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capture [PDF]
Computer Vision and Pattern Recognition, 2022 Due to the visual ambiguity, purely kinematic formulations on monocular human motion capture are often physically incorrect, biomechanically implausible, and can not reconstruct accurate interactions.
Buzhen Huang +4 more
semanticscholar +1 more source