Creating accurate and efficient 3D models poses significant challenges, particularly in addressing large viewpoint variations, computational complexity, and alignment discrepancies. Efficient camera path generation can help resolve these issues. In this context, a modified version of the Affine Scale-Invariant Feature Transform (ASIFT) is proposed to extract more matching points with reduced computational overhead, ensuring an adequate number of inliers for precise camera rotation angle estimation. Additionally, a novel two-camera-based rotation correction model is introduced to mitigate small rotational errors, further enhancing accuracy. Furthermore, a stereo camera-based translation estimation and correction model is implemented to determine camera movement in 3D space by altering the Structure From Motion (SFM) model. Finally, the novel combination of ASIFT and two camera-based SFM models provides an accurate camera movement trajectory in 3D space. Experimental results show that the proposed camera movement approach achieves 99.9% accuracy compared to the actual camera movement path and outperforms state-of-the-art camera path estimation methods. By leveraging this accurate camera path, the system facilitates the creation of precise 3D models, making it a robust solution for applications requiring high fidelity and efficiency in 3D reconstruction.
The Chinese University of Hong Kong(香港中文大学);Johns Hopkins University(约翰斯·霍普金斯大学)
Reconstructing the scene of robotic surgery from the stereo endoscopic video is an important and promising topic in surgical data science, which potentially supports many applications such as surgical visual perception, robotic surgery education and intra-operative context awareness. However, current methods are mostly restricted to reconstructing static anatomy assuming no tissue deformation, tool occlusion and de-occlusion, and camera movement. However, these assumptions are not always satisfied in minimal invasive robotic surgeries. In this work, we present an efficient reconstruction pipel…
Stereo-Inertial Poser: Towards Metric-Accurate Shape-Aware Motion Capture Using Sparse IMUs and a Single Stereo Camera
School of Computer Science, Shanghai Jiao Tong University(上海交通大学计算机科学学院);Meta Robotics Institute, SJTU(SJTU机器人研究院);Shanghai Innovation Institute(上海创新研究院)
SDGE: Stereo Guided Depth Estimation for 360$^\circ$ Camera Sets
School of Computer Science and Technology, Harbin Institute of Technology(哈尔滨工业大学计算机科学与技术学院);SZ DJI Technology Co., Ltd.(深圳市大疆创新科技有限公司);The University of New South Wales(新南威尔士大学)
Aalto University(阿尔托大学);National University of Sciences and Technology(国家科技大学)
We propose a method for fusing stereo disparity estimation with movement-induced prior information. Instead of independent inference frame-by-frame, we formulate the problem as a non-parametric learning task in terms of a temporal Gaussian process prior with a movement-driven kernel for inter-frame reasoning. We present a hierarchy of three Gaussian process kernels depending on the availability of motion information, where our main focus is on a new gyroscope-driven kernel for handheld devices with low-quality MEMS sensors, thus also relaxing the requirement of having full 6D camera poses avai…
Indian Institute of Technology Madras(印度理工学院马德拉斯分校)
Immersive displays such as VR headsets, AR glasses, Multiview displays, Free point televisions have emerged as a new class of display technologies in recent years, offering a better visual experience and viewer engagement as compared to conventional displays. With the evolution of 3D video and display technologies, the consumer market for High Dynamic Range (HDR) cameras and displays is quickly growing. The lack of appropriate experimental data is a critical hindrance for the development of primary research efforts in the field of 3D HDR video technology. Also, the unavailability of sufficient…
Eye-tracking technologies have been widely used in applications like psychological studies and human computer interactions (HCI). However, most current eye trackers focus on 2D point of gaze (PoG) estimation and cannot provide accurate gaze depth.Concerning future applications such as HCI with 3D displays, we propose a novel binocular eye tracking device with stereo stimuli to provide highly accurate 3D PoG estimation. In our device, the 3D stereo imaging system can provide users with a friendly and immersive 3D visual experience without wearing any accessories. The eye capturing system can di…
This study attempts to provide explanations, descriptions and evaluations of some most popular and current combinations of description and descriptor frameworks, namely SIFT, SURF, MSER, and BRISK for keypoint extractors and SIFT, SURF, BRISK, and FREAK for descriptors. Evaluations are made based on the number of matches of keypoints and repeatability in various image variations. It is used as the main parameter to assess how well combinations of algorithms are in matching objects with different variations. There are many papers that describe the comparison of detection and description feature…
DFKI - German Research Center for Artificial Intelligence(德国人工智能研究中心)
This paper demonstrates a system capable of combining a sparse, indirect, monocular visual SLAM, with both offline and real-time Multi-View Stereo (MVS) reconstruction algorithms. This combination overcomes many obstacles encountered by autonomous vehicles or robots employed in agricultural environments, such as overly repetitive patterns, need for very detailed reconstructions, and abrupt movements caused by uneven roads. Furthermore, the use of a monocular SLAM makes our system much easier to integrate with an existing device, as we do not rely on a LiDAR (which is expensive and power consum…
Technische Universität Berlin(柏林工业大学);Einstein Center Digital Future(爱因斯坦数字未来中心);SCIoI Excellence Cluster(SCIoI卓越集群)
This work introduces a co-capture system for multi-animal visual data acquisition using conventional cameras and event cameras. Event cameras offer multiple advantages over frame-based cameras, such as a high temporal resolution and temporal redundancy suppression, which enable us to efficiently capture the fast and erratic movements of fish. We furthermore present an event-based multi-animal tracking algorithm, which proves the feasibility of the approach and sets the baseline for further exploration of combining the advantages of event cameras and conventional cameras for multi-animal tracki…
The development of data innovation as of late and the expanded limit, has permitted the acquaintance of artificial vision connected with SLAM, offering ascend to what is known as Visual SLAM. The objective of this paper is to build up a route framework dependent on Visual SLAM to get a robot to a fundamental and new condition, have the capacity to set and make a three-dimensional guide thereof, utilizing just as sources of info recording your way with a stereo vision camera. The consequence of this analysis is that the framework Visual SLAM together with the combination of Fast SLAM (combinati…
With the developments of dual-lens camera modules,depth information representing the third dimension of thecaptured scenes becomes available for smartphones. It isestimated by stereo matching algorithms, taking as input thetwo views captured by dual-lens cameras at slightly differ-ent viewpoints. Depth-of-field rendering (also be referred toas synthetic defocus or bokeh) is one of the trending depth-based applications. However, to achieve fast depth estima-tion on smartphones, the stereo pairs need to be rectified inthe first place. In this paper, we propose a cost-effective so-lution to perfo…
Free-DyGS: Camera-Pose-Free Scene Reconstruction for Dynamic Surgical Videos with Gaussian Splatting
Department of Biomedical Engineering, National University of Singapore (NUS)(生物医学工程系,新加坡国立大学);National University of Singapore(新加坡国立大学);Yong Loo Lin School of Medicine, NUS(Yong Loo Lin医学院,新加坡国立大学);Department of Surgery, National University Hospital(国立大学医院外科部);Centre for Smart Health, The Hong Kong Polytechnic University(智能健康中心,香港理工大学)
MTA SZTAKI(匈牙利科学院计算机与自动化研究所);Czech Technical University(捷克技术大学)
The technique requires the epipolar geometry to be pre-estimated between each image pair. It exploits the constraints which the camera movement implies, in order to apply a closed-form correction to the parameters of the input affinities. Also, it is shown that the rotations and scales obtained by partially affine-covariant detectors, e.g., AKAZE or SIFT, can be completed to be full affine frames by the proposed algorithm. It is validated both in synthetic experiments and on publicly available real-world datasets that the method always improves the output of the evaluated affine-covariant feat…
Simultaneous hyperkinetic movement disorders phenotyping: a cross-cohort pediatric transfer study using routine videos, markerless pose estimation and a tabular foundation model
Lausanne University Hospital (CHUV)(洛桑大学医院);University of Lausanne (UNIL)(洛桑大学);Institut du Neurone(神经元研究所);Clinique Beau Soleil(博索莱伊诊所);Institut Mutualiste Montpelliérain(蒙彼利埃互助研究所);Military University Hospital of Sfax(斯法克斯军事大学医院);University of Edinburgh(爱丁堡大学);Hospital Sant Joan de Déu(圣琼德迪乌医院);European Reference Network for Rare Neurological Diseases (ERN-RND)(欧洲罕见神经系统疾病参考网络);Instituto de Salud Carlos III(卡洛斯三世健康研究所);CHU Montpellier(蒙彼利埃大学医院);Umeå University(于默奥大学);University Hospital Lausanne(洛桑大学医院);Ecole Polytechnique Fédérale de Lausanne(洛桑联邦理工学院);British Columbia Children’s Hospital(不列颠哥伦比亚儿童医院)
Xidian University(西安电子科技大学);Johns Hopkins University(约翰斯·霍普金斯大学);Xidian Guangzhou Institute of Technology(西安电子科技大学广州研究院)
This paper addresses the challenging unsupervised scene flow estimation problem by jointly learning four low-level vision sub-tasks: optical flow $\textbf{F}$, stereo-depth $\textbf{D}$, camera pose $\textbf{P}$ and motion segmentation $\textbf{S}$. Our key insight is that the rigidity of the scene shares the same inherent geometrical structure with object movements and scene depth. Hence, rigidity from $\textbf{S}$ can be inferred by jointly coupling $\textbf{F}$, $\textbf{D}$ and $\textbf{P}$ to achieve more robust estimation. To this end, we propose a novel scene flow framework named EffiSc…