0000000000970047
AUTHOR
Danda Pani Paudel
showing 12 related works from this author
High Quality Reconstruction of Dynamic Objects using 2D-3D Camera Fusion
2017
International audience; In this paper, we propose a complete pipeline for high quality reconstruction of dynamic objects using 2D-3D camera setup attached to a moving vehicle. Starting from the segmented motion trajectories of individual objects, we compute their precise motion parameters, register multiple sparse point clouds to increase the density, and develop a smooth and textured surface from the dense (but scattered) point cloud. The success of our method relies on the proposed optimization framework for accurate motion estimation between two sparse point clouds. Our formulation for fusing it closest-point and it consensus based motion estimations, respectively in the absence and pres…
Incomplete 3D motion trajectory segmentation and 2D-to-3D label transfer for dynamic scene analysis
2017
International audience; The knowledge of the static scene parts and the moving objects in a dynamic scene plays a vital role for scene modelling, understanding, and landmark-based robot navigation. The key information for these tasks lies on semantic labels of the scene parts and the motion trajectories of the dynamic objects. In this work, we propose a method that segments the 3D feature trajectories based on their motion behaviours, and assigns them semantic labels using 2D-to-3D label transfer. These feature trajectories are constructed by using the proposed trajectory recovery algorithm which takes the loss of feature tracking into account. We introduce a complete framework for static-m…
Unsupervised learning of category-specific symmetric 3D keypoints from point sets
2020
Lecture Notes in Computer Science, 12370
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Static and Dynamic Objects Analysis as a 3D Vector Field
2017
International audience; In the context of scene modelling, understanding, and landmark-based robot navigation, the knowledge of static scene parts and moving objects with their motion behaviours plays a vital role. We present a complete framework to detect and extract the moving objects to reconstruct a high quality static map. For a moving 3D camera setup, we propose a novel 3D Flow Field Analysis approach which accurately detects the moving objects using only 3D point cloud information. Further, we introduce a Sparse Flow Clustering approach to effectively and robustly group the motion flow vectors. Experiments show that the proposed Flow Field Analysis algorithm and Sparse Flow Clusterin…
Localization of 2D Cameras in a Known Environment Using Direct 2D-3D Registration
2014
International audience; In this paper we propose a robust and direct 2D-to- 3D registration method for localizing 2D cameras in a known 3D environment. Although the 3D environment is known, localizing the cameras remains a challenging problem that is particularly undermined by the unknown 2D-3D correspondences, outliers, scale ambiguities and occlusions. Once the cameras are localized, the Structure-from-Motion reconstruction obtained from image correspondences is refined by means of a constrained nonlinear optimization that benefits from the knowledge of the scene. We also propose a common optimization framework for both localization and refinement steps in which projection errors in one v…
Efficient Pruning LMI Conditions for Branch-and-Prune Rank and Chirality-Constrained Estimation of the Dual Absolute Quadric
2014
International audience; We present a new globally optimal algorithm for self- calibrating a moving camera with constant parameters. Our method aims at estimating the Dual Absolute Quadric (DAQ) under the rank-3 and, optionally, camera centers chirality constraints. We employ the Branch-and-Prune paradigm and explore the space of only 5 parameters. Pruning in our method relies on solving Linear Matrix Inequality (LMI) feasibility and Generalized Eigenvalue (GEV) problems that solely depend upon the entries of the DAQ. These LMI and GEV problems are used to rule out branches in the search tree in which a quadric not satisfy- ing the rank and chirality conditions on camera centers is guarantee…
Robust RGB-D Fusion for Saliency Detection
2022
Efficiently exploiting multi-modal inputs for accurate RGB-D saliency detection is a topic of high interest. Most existing works leverage cross-modal interactions to fuse the two streams of RGB-D for intermediate features' enhancement. In this process, a practical aspect of the low quality of the available depths has not been fully considered yet. In this work, we aim for RGB-D saliency detection that is robust to the low-quality depths which primarily appear in two forms: inaccuracy due to noise and the misalignment to RGB. To this end, we propose a robust RGB-D fusion method that benefits from (1) layer-wise, and (2) trident spatial, attention mechanisms. On the one hand, layer-wise atten…
2D-3D Camera Fusion for Visual Odometry in Outdoor Environments
2014
International audience; Accurate estimation of camera motion is very important for many robotics applications involving SfM and visual SLAM. Such accuracy is attempted by refining the estimated motion through nonlinear optimization. As many modern robots are equipped with both 2D and 3D cameras, it is both highly desirable and challenging to exploit data acquired from both modalities to achieve a better localization. Existing refinement methods, such as Bundle adjustment and loop closing, may be employed only when precise 2D-to-3D correspondences across frames are available. In this paper, we propose a framework for robot localization that benefits from both 2D and 3D information without re…
3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image Fusion
2016
International audience; Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point (ICP) registration technique or its variances are not accurate and rob…
Reconstruction 3D de scènes dynamiques par segmentation au sens du mouvement
2016
National audience; L'objectif de ce travail est de reconstruire les parties sta-tiques et dynamiques d'une scène 3D à l'aide d'un robot mobile équipé d'un capteur 3D. Cette reconstruction né-cessite la classification des points 3D acquis au cours du temps en point fixe et point mobile indépendamment du dé-placement du robot. Notre méthode de segmentation utilise directement les données 3D et étudie les mouvements des objets dans la scène sans hypothèse préalable. Nous déve-loppons un algorithme complet reconstruisant les parties fixes de la scène à chaque acquisition à l'aide d'un RAN-SAC qui ne requiert que 3 points pour recaler les nuages de points. La méthode a été expérimentée sur de la…
Estimation de la pose d'une caméra dans un environnement connu à partir d'un recalage 2D-3D
2014
National audience; Nous proposons une méthode directe de recalage robuste 2D-3D permettant de localiser une caméra dans un environnement 3D connu. Il s'agit d'un problème rendu particulièrement difficile par l'absence de correspondances entre les points 3D du nuage et les points 2D. A cette difficulté, s'ajoute la différence d'échelle entre le nuage 3D connu et le nuage 3D reconstruit à partir d'images qui, de plus, peut contenir des points aberrants et des occultations. Notre méthode consiste en l'optimisation d'une fonctionnelle de manière itérative en deux étapes : estimation de la pose de la caméra et mise en correspondance 2D-3D. Ainsi, nous obtenons une méthode d'estimation conjointe …