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In this paper, we present a novel framework designed to reconstruct long-sequence 3D human motion in the world coordinates from in-the-wild videos with multiple shot transitions. Such long-sequence in-the-wild motions are highly valuable to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yuhong Zhang , Guanlin Wu , Ling-Hao Chen , Zhuokai Zhao , Jing Lin , Xiaoke Jiang , Jiamin Wu , Zhuoheng Li , Hao Frank Yang , Haoqian Wang , Lei Zhang

In this paper, we introduce a method for reconstructing 3D humans from a single image using a biomechanically accurate skeleton model. To achieve this, we train a transformer that takes an image as input and estimates the parameters of the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yan Xia , Xiaowei Zhou , Etienne Vouga , Qixing Huang , Georgios Pavlakos

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…

Computer Vision and Pattern Recognition · Computer Science 2016-05-27 Alireza Shafaei , James J. Little

Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Nyquist rate. Despite significant progress in the theory and methods of…

Computer Vision and Pattern Recognition · Computer Science 2013-06-27 Aswin C Sankaranarayanan , Pavan K Turaga , Rama Chellappa , Richard G Baraniuk

Full-body motion tracking plays an essential role in AR/VR applications, bridging physical and virtual interactions. However, it is challenging to reconstruct realistic and diverse full-body poses based on sparse signals obtained by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Shuting Zhao , Zeyu Xiao , Xinrong Chen

We propose to learn a probabilistic motion model from a sequence of images. Besides spatio-temporal registration, our method offers to predict motion from a limited number of frames, useful for temporal super-resolution. The model is based…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Julian Krebs , Tommaso Mansi , Nicholas Ayache , Hervé Delingette

In this paper we present a new approach for marker less human motion capture from conventional camera feeds. The aim of our study is to recover 3D positions of key points of the body that can serve for gait analysis. Our approach is based…

Artificial Intelligence · Computer Science 2007-05-23 Jamal Saboune , François Charpillet

The use of drones for aerial cinematography has revolutionized several applications and industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely controlling a drone while…

Robotics · Computer Science 2019-07-30 Rogerio Bonatti , Cherie Ho , Wenshan Wang , Sanjiban Choudhury , Sebastian Scherer

Creating scenes for captured motions that achieve realistic human-scene interaction is crucial for 3D animation in movies or video games. As character motion is often captured in a blue-screened studio without real furniture or objects in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Jianan Li , Tao Huang , Qingxu Zhu , Tien-Tsin Wong

Motion capture systems are a widespread tool in research to record ground-truth poses of objects. Commercial systems use reflective markers attached to the object and then triangulate pose of the object from multiple camera views.…

Robotics · Computer Science 2025-02-18 Leonard Bauersfeld , Davide Scaramuzza

Monocular depth reconstruction of complex and dynamic scenes is a highly challenging problem. While for rigid scenes learning-based methods have been offering promising results even in unsupervised cases, there exists little to no…

Computer Vision and Pattern Recognition · Computer Science 2021-10-29 Ayça Takmaz , Danda Pani Paudel , Thomas Probst , Ajad Chhatkuli , Martin R. Oswald , Luc Van Gool

This paper looks into the problem of pedestrian tracking using a monocular, potentially moving, uncalibrated camera. The pedestrians are located in each frame using a standard human detector, which are then tracked in subsequent frames.…

Computer Vision and Pattern Recognition · Computer Science 2015-01-27 Sourav Garg , Swagat Kumar , Rajesh Ratnakaram , Prithwijit Guha

Recent advances in image-based human pose estimation make it possible to capture 3D human motion from a single RGB video. However, the inherent depth ambiguity and self-occlusion in a single view prohibit the recovery of as high-quality…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Junting Dong , Qing Shuai , Yuanqing Zhang , Xian Liu , Xiaowei Zhou , Hujun Bao

Whole-body humanoid motion represents a fundamental challenge in robotics, requiring balance, coordination, and adaptability to enable human-like behaviors. However, existing methods typically require multiple training samples per motion,…

In this paper, we tackle the problem of estimating the depth of a scene from a monocular video sequence. In particular, we handle challenging scenarios, such as non-translational camera motion and dynamic scenes, where traditional structure…

Computer Vision and Pattern Recognition · Computer Science 2015-11-20 Miaomiao Liu , Mathieu Salzmann , Xuming He

This paper describes the kinematics of the motion tracking of a rigid body using video recording. The novelty of the paper is on the adaptation of the methods and nomenclature used in Computer Vision to those used in Multibody System…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 José L. Escalona

In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the…

Computer Vision and Pattern Recognition · Computer Science 2007-08-21 Oliver Knill , Jose Ramirez-Herran

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack of temporally consistent handling of plausible clothing…

Computer Vision and Pattern Recognition · Computer Science 2020-12-22 Moritz Kappel , Vladislav Golyanik , Mohamed Elgharib , Jann-Ole Henningson , Hans-Peter Seidel , Susana Castillo , Christian Theobalt , Marcus Magnor

It is at times important to detect human presence automatically in secure environments. This needs a shape recognition algorithm that is robust, fast and has low error rates. The algorithm needs to process camera images quickly to detect…

Computer Vision and Pattern Recognition · Computer Science 2015-06-30 Dhriti Sengupta , Merina Kundu , Jayati Ghosh Dastidar

We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes. Most conventional structure from motion and monocular SLAM techniques assume input…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Zhengqi Li , Richard Tucker , Forrester Cole , Qianqian Wang , Linyi Jin , Vickie Ye , Angjoo Kanazawa , Aleksander Holynski , Noah Snavely
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