3-D Object Model Recovery From 2-D Images Using Structured Light

Lavoie, Philippe; Ionescu, Dan; Petriu, Emil M.

doi:10.1109/tim.2004.823320

Cited by 48 publications

(27 citation statements)

References 2 publications

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“…Other related works include Lavoie et al [6] and Pagès et al [7]. Their methods are similar to ours in that they use only one light pattern and take a single image of the illuminated object.…”

Section: Related Workmentioning

confidence: 89%

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Robust Dense Depth Acquisition Using 2-D De Bruijn Structured Light

Tan

2007

Entertainment Computing – ICEC 2007

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Abstract. We present a new dense depth acquisition method using 2-D De Bruijn structured light, which is robust to various textures and is able to reconstruct dense depth maps of moving and deforming objects. A 2-D binary De Bruijn pattern is emitted to the target object by an off-the-shelf projector. Fast dynamic programming based stereo matching is performed on images taken from two different views. The depth is obtained by robust least square triangulation. The advantages include that we do not need to take image sequences with different illumination patterns and do not assume that the surface for reconstruction has uniform texture. Experimental results show that shapes can be efficiently obtained in good quality by the proposed approach. We believe that our approach is a good choice in applications of acquiring depth maps for moving scenes with inexpensive equipments.

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Section: Related Workmentioning

confidence: 89%

“…Their methods are similar to ours in that they use only one light pattern and take a single image of the illuminated object. However, Lavoie et al [6] encode the structured light on the intersections of a grid pattern, and match the code only where reliable decoding is available. Thus a sparse reconstruction is obtained as the result.…”

Section: Related Workmentioning

confidence: 99%

Robust Dense Depth Acquisition Using 2-D De Bruijn Structured Light

Tan

2007

Entertainment Computing – ICEC 2007

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“…A more practical way to obtain the 3D information of a curved object in real time is the structured light technique. [11], [14], [15] This technique utilizes a projector to project a known light pattern onto an object. The light pattern on the object is then viewed from a camera mounted next to the projector.…”

Section: Miniaturized Force-indentation Depth Sensor For Tissue Abnormentioning

confidence: 99%

Miniaturized force-indentation depth sensor for tissue abnormality identification during laparoscopic surgery

Liu

Poon

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-This paper presents a novel miniaturized force-indentation depth (FID) sensor designed to conduct indentation on soft tissue during minimally invasive surgery. It can intra-operatively aid the surgeon to rapidly identify the tissue abnormalities within the tissue. The FID sensor can measure the indentation depth of a semi-spherical indenter and the tissue reaction force simultaneously. It make use of with fiber optical fiber sensing method measure indentation depth and force and is small enough to fit through a standard trocar port with a diameter of 11 mm.The created FID sensor was calibrated and tested on silicone block simulating soft tissue. The results show that the sensor can measure the indentation depth accurately and also the orientation of the sensor with respect to the tissue surface whilst performing indentation. . I. INTRODUCTIONThere ). Distinct advantages of these robotic systems include high distal dexterity, enhanced 3D vision, motion scaling and tremor filtering as well as direct hand-eye coordination eliminating reversed tool motions. These advances result in improved ergonomics and also allow complex surgical procedures, which are usually difficult to be conducted by conventional minimally invasive means such as coronary artery bypass grafting [3] and mitral valve repair[4] to be effectively performed. However, the lack of haptic feedback in current robot-aided minimally invasive surgery systems is still one of the major downsides of such systems.Manuscript

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“…However, very often the reconstruction process bases on an expensive camera [2], specialist equipment such as a depth camera [3], or structured light [4].…”

Section: Introductionmentioning

confidence: 99%

3D model reconstruction and evaluation using a collection of points extracted from the series of photographs

Rzazewska¹,

Luckner²

2014

Annals of Computer Science and Information Systems

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Abstract-This work describes the whole process of 3D model reconstruction. It begins with the representation of the method that is used to find the matching between photographs and the methodology to use the data to form the initial structure of the reconstructed model, represented by a point cloud. As a next stage, a refinement process is performed, using the bundle adjustment method. A set of stereovision methods is used later on to find a more detailed solution. Those algorithms use pairs of images, therefore as a prerequisite a set of routines that aggregates those results is studied. The paper is concluded with a description of how the point cloud is processed, including the surface reconstruction, to form the result. The described methodology is illustrated with reconstructions of three series of professional photographs from a public repository and one series of amateur photographs created especially for this work. The results were evaluated by the proposed area matching and contour matching measures.

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3-D Object Model Recovery From 2-D Images Using Structured Light

Cited by 48 publications

References 2 publications

Robust Dense Depth Acquisition Using 2-D De Bruijn Structured Light

Robust Dense Depth Acquisition Using 2-D De Bruijn Structured Light

Miniaturized force-indentation depth sensor for tissue abnormality identification during laparoscopic surgery

3D model reconstruction and evaluation using a collection of points extracted from the series of photographs

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