3,487 research outputs found
3D Object Reconstruction from Hand-Object Interactions
Recent advances have enabled 3d object reconstruction approaches using a
single off-the-shelf RGB-D camera. Although these approaches are successful for
a wide range of object classes, they rely on stable and distinctive geometric
or texture features. Many objects like mechanical parts, toys, household or
decorative articles, however, are textureless and characterized by minimalistic
shapes that are simple and symmetric. Existing in-hand scanning systems and 3d
reconstruction techniques fail for such symmetric objects in the absence of
highly distinctive features. In this work, we show that extracting 3d hand
motion for in-hand scanning effectively facilitates the reconstruction of even
featureless and highly symmetric objects and we present an approach that fuses
the rich additional information of hands into a 3d reconstruction pipeline,
significantly contributing to the state-of-the-art of in-hand scanning.Comment: International Conference on Computer Vision (ICCV) 2015,
http://files.is.tue.mpg.de/dtzionas/In-Hand-Scannin
SegICP: Integrated Deep Semantic Segmentation and Pose Estimation
Recent robotic manipulation competitions have highlighted that sophisticated
robots still struggle to achieve fast and reliable perception of task-relevant
objects in complex, realistic scenarios. To improve these systems' perceptive
speed and robustness, we present SegICP, a novel integrated solution to object
recognition and pose estimation. SegICP couples convolutional neural networks
and multi-hypothesis point cloud registration to achieve both robust pixel-wise
semantic segmentation as well as accurate and real-time 6-DOF pose estimation
for relevant objects. Our architecture achieves 1cm position error and
<5^\circ$ angle error in real time without an initial seed. We evaluate and
benchmark SegICP against an annotated dataset generated by motion capture.Comment: IROS camera-read
Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery
One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions
One-To-One Scale Modeling For 3D Printing
Current methods of 3D shape acquisition do not take into account the size of the object unless expensive laser scanning equipment is used. This thesis provides details on the design and implementation of creating a 3D model to size for 3D printing. The thesis explores a pipeline using depth information gathered from a Microsoft Kinect and various open source software and freeware. The algorithms and techniques that are utilized to create the 3D models are also described. VisualSFM's point cloud generator, Meshlab's Poisson surface reconstructor, and Microsoft's 3D Builder are some of the pipeline components used in the research. Results obtained at different stages of the process will be presented and discussed
Virtual Reality applied to biomedical engineering
Actualment, la realitat virtual esta sent tendència i s'està expandint a l'àmbit mèdic, fent possible l'aparició de nombroses aplicacions dissenyades per entrenar metges i tractar pacients de forma més eficient, així com optimitzar els processos de planificació quirúrgica. La necessitat mèdica i objectiu d'aquest projecte és fer òptim el procés de planificació quirúrgica per a cardiopaties congènites, que compren la reconstrucció en 3D del cor del pacient i la seva integració en una aplicació de realitat virtual. Seguint aquesta línia s’ha combinat un procés de modelat 3D d’imatges de cors obtinguts gracies al Hospital Sant Joan de Déu i el disseny de l’aplicació mitjançant el software Unity 3D gracies a l’empresa VISYON. S'han aconseguit millores en quant al software emprat per a la segmentació i reconstrucció, i s’han assolit funcionalitats bàsiques a l’aplicació com importar, moure, rotar i fer captures de pantalla en 3D de l'òrgan cardíac i així, entendre millor la cardiopatia que s’ha de tractar. El resultat ha estat la creació d'un procés òptim, en el que la reconstrucció en 3D ha aconseguit ser ràpida i precisa, el mètode d’importació a l’app dissenyada molt senzill, i una aplicació que permet una interacció atractiva i intuïtiva, gracies a una experiència immersiva i realista per ajustar-se als requeriments d'eficiència i precisió exigits en el camp mèdic
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