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Related papers: Human Motion Capture Using a Drone

200 papers

In this paper, a marker-based, single-person optical motion capture method (DeepMoCap) is proposed using multiple spatio-temporally aligned infrared-depth sensors and retro-reflective straps and patches (reflectors). DeepMoCap explores…

Computer Vision and Pattern Recognition · Computer Science 2021-10-15 Anargyros Chatzitofis , Dimitrios Zarpalas , Stefanos Kollias , Petros Daras

Training state-of-the-art models for human body pose and shape recovery from images or videos requires datasets with corresponding annotations that are really hard and expensive to obtain. Our goal in this paper is to study whether poses…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Fabien Baradel , Thibault Groueix , Philippe Weinzaepfel , Romain Brégier , Yannis Kalantidis , Grégory Rogez

Markerless human motion capture (mocap) from multiple RGB cameras is a widely studied problem. Existing methods either need calibrated cameras or calibrate them relative to a static camera, which acts as the reference frame for the mocap…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Nitin Saini , Chun-hao P. Huang , Michael J. Black , Aamir Ahmad

We introduce a novel motion capture system that reconstructs full-body 3D motion using only sparse pairwise distance (PWD) measurements from body-mounted(UWB) sensors. Using time-of-flight ranging between wireless nodes, our method…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Ofir Abramovich , Ariel Shamir , Andreas Aristidou

Existing human Motion Capture (MoCap) methods mostly focus on the visual similarity while neglecting the physical plausibility. As a result, downstream tasks such as driving virtual human in 3D scene or humanoid robots in real world suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Shenghao Ren , Yi Lu , Jiayi Huang , Jiayi Zhao , He Zhang , Tao Yu , Qiu Shen , Xun Cao

We propose a novel hybrid calibration-free method FreeCap to accurately capture global multi-person motions in open environments. Our system combines a single LiDAR with expandable moving cameras, allowing for flexible and precise motion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Aoru Xue , Yiming Ren , Zining Song , Mao Ye , Xinge Zhu , Yuexin Ma

Marker-based motion capture (MoCap) systems can be composed by several dozens of cameras with the purpose of reconstructing the trajectories of hundreds of targets. With a large amount of cameras it becomes interesting to determine the…

Computer Vision and Pattern Recognition · Computer Science 2012-03-16 Andrea Masiero , Angelo Cenedese

In this letter, we present a novel markerless 3D human motion capture (MoCap) system for unstructured, outdoor environments that uses a team of autonomous unmanned aerial vehicles (UAVs) with on-board RGB cameras and computation. Existing…

Computer Vision and Pattern Recognition · Computer Science 2022-04-27 Nitin Saini , Elia Bonetto , Eric Price , Aamir Ahmad , Michael J. Black

This article addresses collaborative 3D map reconstruction using multiple drones. Achieving high-quality reconstruction requires capturing images of keypoints within the target scene from diverse viewing angles, and coverage control offers…

Robotics · Computer Science 2025-10-22 Muhammad Hanif , Reiji Terunuma , Takumi Sumino , Kelvin Cheng , Takeshi Hatanaka

Monocular 3D motion capture (mocap) is beneficial to many applications. The use of a single camera, however, often fails to handle occlusions of different body parts and hence it is limited to capture relatively simple movements. We present…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Han Liang , Yannan He , Chengfeng Zhao , Mutian Li , Jingya Wang , Jingyi Yu , Lan Xu

This paper addresses the problem of 3D human pose estimation in the wild. A significant challenge is the lack of training data, i.e., 2D images of humans annotated with 3D poses. Such data is necessary to train state-of-the-art CNN…

Computer Vision and Pattern Recognition · Computer Science 2016-10-31 Grégory Rogez , Cordelia Schmid

We present a lightweight and affordable motion capture method based on two smartwatches and a head-mounted camera. In contrast to the existing approaches that use six or more expert-level IMU devices, our approach is much more…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Jiye Lee , Hanbyul Joo

In the rapidly evolving landscape of digital content creation, the demand for fast, convenient, and autonomous methods of crafting detailed 3D reconstructions of humans has grown significantly. Addressing this pressing need, our AirNeRF…

Robotics · Computer Science 2024-07-16 Alexey Kotcov , Maria Dronova , Vladislav Cheremnykh , Sausar Karaf , Dzmitry Tsetserukou

Learning-based approaches to monocular motion capture have recently shown promising results by learning to regress in a data-driven manner. However, due to the challenges in data collection and network designs, it remains challenging for…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yuxiang Zhang , Hongwen Zhang , Liangxiao Hu , Jiajun Zhang , Hongwei Yi , Shengping Zhang , Yebin Liu

Motion capture (mocap) and time-of-flight based sensing of human actions are becoming increasingly popular modalities to perform robust activity analysis. Applications range from action recognition to quantifying movement quality for health…

Computer Vision and Pattern Recognition · Computer Science 2020-12-04 Suhas Lohit , Rushil Anirudh , Pavan Turaga

Marker-less 3D human motion capture from a single colour camera has seen significant progress. However, it is a very challenging and severely ill-posed problem. In consequence, even the most accurate state-of-the-art approaches have…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Soshi Shimada , Vladislav Golyanik , Weipeng Xu , Christian Theobalt

Generating realistic full-body motion interacting with objects is critical for applications in robotics, virtual reality, and human-computer interaction. While existing methods can generate full-body motion within 3D scenes, they often lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Kunal Bhosikar , Siddharth Katageri , Vivek Madhavaram , Kai Han , Charu Sharma

The paper proposes a novel concept of docking drones to make this process as safe and fast as possible. The idea behind the project is that a robot with a soft gripper grasps the drone in midair. The human operator navigates the robotic arm…

We present a method to reconstruct the 3D trajectory of an airborne robotic system only from videos recorded with cameras that are unsynchronized, may feature rolling shutter distortion, and whose viewpoints are unknown. Our approach…

Robotics · Computer Science 2020-07-30 Jingtong Li , Jesse Murray , Dorina Ismaili , Konrad Schindler , Cenek Albl

The task of reconstructing 3D human motion has wideranging applications. The gold standard Motion capture (MoCap) systems are accurate but inaccessible to the general public due to their cost, hardware and space constraints. In contrast,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-29 Kuan-Chieh Wang , Zhenzhen Weng , Maria Xenochristou , Joao Pedro Araujo , Jeffrey Gu , C. Karen Liu , Serena Yeung