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Rolling-shutter (RS) cameras are ubiquitous, but RS SfM (structure-from-motion) has not been fully solved yet. This work suggests an approach to remedy this: We characterize RS single-view geometry of observed world points or lines.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Sofía Errázuriz Muñoz , Kim Kiehn , Petr Hruby , Kathlén Kohn

Establishing correspondences across images is a fundamental challenge in computer vision, underpinning tasks like Structure-from-Motion, image editing, and point tracking. Traditional methods are often specialized for specific…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Fei Xue , Sven Elflein , Laura Leal-Taixé , Qunjie Zhou

We introduce TAPIP3D, a novel approach for long-term 3D point tracking in monocular RGB and RGB-D videos. TAPIP3D represents videos as camera-stabilized spatio-temporal feature clouds, leveraging depth and camera motion information to lift…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Bowei Zhang , Lei Ke , Adam W. Harley , Katerina Fragkiadaki

In this paper, we deal with the problem to predict the future 3D motions of 3D object scans from previous two consecutive frames. Previous methods mostly focus on sparse motion prediction in the form of skeletons. While in this paper we…

Computer Vision and Pattern Recognition · Computer Science 2020-06-25 Shuaihang Yuan , Xiang Li , Anthony Tzes , Yi Fang

3D multi-object tracking aims to uniquely and consistently identify all mobile entities through time. Despite the rich spatiotemporal information available in this setting, current 3D tracking methods primarily rely on abstracted…

Computer Vision and Pattern Recognition · Computer Science 2022-07-14 Colton Stearns , Davis Rempe , Jie Li , Rares Ambrus , Sergey Zakharov , Vitor Guizilini , Yanchao Yang , Leonidas J Guibas

In this paper we address a classification problem that has not been considered before, namely motion segmentation given pairwise matches only. Our contribution to this unexplored task is a novel formulation of motion segmentation as a…

Computer Vision and Pattern Recognition · Computer Science 2019-05-23 Federica Arrigoni , Tomas Pajdla

We study analogical trajectory transfer, where the goal is to translate motion trajectories in one 3D environment to a semantically analogous location in another. Such a capacity would enable machines to perform analogical spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Junho Kim , Eun Sun Lee , Gwangtak Bae , Seunggu Kang , Young Min Kim

This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification. We first introduce a boosting-based approach to learn a correspondence structure which…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Weiyao Lin , Yang Shen , Junchi Yan , Mingliang Xu , Jianxin Wu , Jingdong Wang , Ke Lu

Point tracking aims to identify the same physical point across video frames and serves as a geometry-aware representation of motion. This representation supports a wide range of applications, from robotics to augmented reality, by enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Görkay Aydemir

This paper presents a novel approach of representing dynamic visual scenes with static maps generated from video/image streams. Such representation allows easy visual assessment of motion in dynamic environments. These maps are 2D matrices…

Computer Vision and Pattern Recognition · Computer Science 2021-03-05 Bruno Costa , Enrique Corona , Mostafa Parchami , Gint Puskorius , Dimitar Filev

Structure from Motion (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is contingent on the accuracy of those estimates, is reduced. One…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Victor Amblard , Timothy P. Osedach , Arnaud Croux , Andrew Speck , John J. Leonard

The Structure from Motion (SfM) challenge in computer vision is the process of recovering the 3D structure of a scene from a series of projective measurements that are calculated from a collection of 2D images, taken from different…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Joseph Rowell

Methods tackling multi-object tracking need to estimate the number of targets in the sensing area as well as to estimate their continuous state. While the majority of existing methods focus on data association, precise state (3D pose)…

Computer Vision and Pattern Recognition · Computer Science 2019-10-11 Johannes Groß , Aljosa Osep , Bastian Leibe

Traditional point tracking algorithms such as the KLT use local 2D information aggregation for feature detection and tracking, due to which their performance degrades at the object boundaries that separate multiple objects. Recently, CoMaL…

Computer Vision and Pattern Recognition · Computer Science 2017-06-09 Santhosh K. Ramakrishnan , Swarna Kamlam Ravindran , Anurag Mittal

Real-time video analysis remains a challenging problem in computer vision, requiring efficient processing of both spatial and temporal information while maintaining computational efficiency. Existing approaches often struggle to balance…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Shahla John

Most existing Multi-Object Tracking (MOT) approaches follow the Tracking-by-Detection paradigm and the data association framework where objects are firstly detected and then associated. Although deep-learning based method can noticeably…

Computer Vision and Pattern Recognition · Computer Science 2020-07-14 Xingyu Wan , Jiakai Cao , Sanping Zhou , Jinjun Wang

3D lanes offer a more comprehensive understanding of the road surface geometry than 2D lanes, thereby providing crucial references for driving decisions and trajectory planning. While many efforts aim to improve prediction accuracy, we…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Haibin Zhou , Huabing Zhou , Jun Chang , Tao Lu , Jiayi Ma

Recovering dense and long-range pixel motion in videos is a challenging problem. Part of the difficulty arises from the 3D-to-2D projection process, leading to occlusions and discontinuities in the 2D motion domain. While 2D motion can be…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yuxi Xiao , Qianqian Wang , Shangzhan Zhang , Nan Xue , Sida Peng , Yujun Shen , Xiaowei Zhou

Augmented reality assembly guidance is essential for intelligent manufacturing and medical applications, requiring continuous measurement of the 6DoF poses of manipulated objects. Although current tracking methods have made significant…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Jixiang Chen , Jing Chen , Kai Liu , Haochen Chang , Shanfeng Fu , Jian Yang

Optical motion capture systems have become a widely used technology in various fields, such as augmented reality, robotics, movie production, etc. Such systems use a large number of cameras to triangulate the position of optical markers.The…

Machine Learning · Computer Science 2018-09-26 Taras Kucherenko , Jonas Beskow , Hedvig Kjellström
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