Shape Recovery of Endoscopic Videos by Shape from Shading Using Mesh Regularization

2017 ◽  
pp. 204-213
Author(s):  
Zhihang Ren ◽  
Tong He ◽  
Lingbing Peng ◽  
Shuaicheng Liu ◽  
Shuyuan Zhu ◽  
...  
Keyword(s):  
Shape Recovery ◽  
Shape From Shading ◽  
Endoscopic Videos

scholarly journals Polyp Shape Recovery from Single Endoscope Image using Medical Suture

2019 ◽  
Vol 12 (1) ◽  
pp. 1-17
Author(s):  
Hiroyasu Usami ◽  
Yuji Iwahori ◽  
Aili Wang ◽  
M. K. Bhuyan ◽  
Naotaka Ogasawara ◽  
...  
Keyword(s):  
Support System ◽  
Shape Recovery ◽  
Shape From Shading ◽  
Surface Reflectance ◽  
Absolute Size ◽  
Recovery Method ◽  
Constraint Equations ◽  
Medical Structure ◽  
Reflectance Factor ◽  
Lambertian Reflectance

Background:Polyp shapes play an important role in colorectal diagnosis. However, endoscopy images are usually composed of nonrigid objects such as a polyp. Hence, it is challenging for polyp shape recovery. It is demanded to establish a support system of the colorectal diagnosis system based on polyp shape.Introduction:Shape from Shading (SFS) is one valuable approach based on photoclinometry for polyp shape recovery. SFS and endoscope image are compatible on the first sight, but there are constraints for applying SFS to endoscope image. Those approaches need some parameters like a depth from the endoscope lens to the surface, and surface reflectance factor . Furthermore, those approaches assume the whole surface which has the same value of for the Lambertian surface.Methods:This paper contributes to mitigating constraint for applying SFS to the endoscope image based on a cue from the medical structure. An extracted medical suture is used to estimate parameters, and a method of polyp shape recovery method is proposed using both geometric and photometric constraint equations. Notably, the proposed method realizes polyp shape recovery from a single endoscope image.Results:From experiments it was confirmed that the approximate polyp model shape was recovered and the proposed method recovered absolute size and shape of polyp using medical suture information and obtained parameters from a single endoscope image.Conclusion:This paper proposed a polyp shape recovery method which mitigated the constraint for applying SFS to the endoscope image using the medical suture. Notably, the proposed method realized polyp shape recovery from a single endoscope image without generating uniform Lambertian reflectance.

Towards Developing a Practical System to Recover Light, Reflectance and Shape

1997 ◽  
Vol 11 (06) ◽  
pp. 991-1022 ◽  
Author(s):  
Sanjay Bakshi ◽  
Yee-Hong Yang
Keyword(s):  
Shape Recovery ◽  
Three Dimensional ◽  
Shape From Shading ◽  
Modular System ◽  
Surface Reflectance ◽  
Shape Information ◽  
Light Reflectance ◽  
Dimensional Shape ◽  
Lambertian Reflectance ◽  
Point Light

Due to the complexity of the shape-from-shading problem, most solutions rely on idealistic conditions. Orthographic imaging, a known distant point light source, and known surface reflectance properties are usually assumed. Furthermore, most real surfaces are neither perfectly diffuse (Lambertian) nor ideally specular (mirror-like); however most shape-from-shading algorithms assume Lambertian reflectance. The behavior of shape-from-shading algorithms that rely on idealistic conditions is unpredictable in real imaging situations. In this paper, the LIRAS (LIght, Reflectance, And Shape) Recovery System is proposed. LIRAS is a practical approach to the shape-from-shading problem, as many of these assumptions are relaxed. LIRAS is also a modular system: there is a component that recovers the surface reflectance properties, thus the assumption of Lambertian reflectance is relaxed. Rather than assume a known illuminant direction, a component exists that can recover the light orientation. Once the reflectance map is determined, another LIRAS module can use this information to recover the shape for non-Lambertian surfaces. Each of these modules is described and a discussion of how the components cooperate to recover three-dimensional shape information in real environments is given. Extensive experimental evaluation is conducted using both synthetic and real images and the results are very encouraging. The contributions of this paper include the design and implementation of LIRAS and the extensive quantative and qualitative experimental results, which can provide guidelines for future refinements of other shape recovery systems.

scholarly journals REFINEMENT OF STEREO IMAGE ANALYSIS USING PHOTOMETRIC SHAPE RECOVERY AS AN ALTERNATIVE TO BUNDLE ADJUSTMENT

2016 ◽  
Vol XLI-B4 ◽  
pp. 565-572
Author(s):  
A. Grumpe ◽  
C. Schröer ◽  
S. Kauffmann ◽  
T. Fricke ◽  
C. Wöhler ◽  
...  
Keyword(s):  
Image Analysis ◽  
Shape Recovery ◽  
Shape From Shading ◽  
Bundle Adjustment ◽  
Stereo Image ◽  
General Interest ◽  
Multiple Images ◽  
Digital Elevation ◽  
High Lateral Resolution ◽  
3D Information

Topographic mapping, e.g. the generation of Digital Elevation Models (DEM), is of general interest to the remote sensing community and scientific research. Commonly, photogrammetric methods, e.g. stereo image analysis methods (SIAM) or bundle adjustment methods (BAM), are applied to derive 3D information based on multiple images of an area. These methods require the detection of control points, i.e. common points within multiple images, which relies on a similarity measure and usually yields a sparse map of 3D points. The full spatial DEM is then obtained by interpolation techniques or imposed restrictions, e.g. smoothness constraints. Since BAM utilizes all images of the area, it is assumed to provide a more accurate DEM than SIAM which utilizes only pairs of images. Intensity-based shape recovery, e.g. shape from shading (SfS), utilizes the reflectance behavior of the object surface and thus provides a dense map of relative height changes, which provide the possibility to refine the photogrammetric DEMs. Based on Rosetta NavCam images of 67P/Churyumov-Gerasimenko we compare intensity-based DEM refinement methods which use DEMs obtained based on SIAM and BAM as a reference. We show that both the SIAM based DEM refinement and the BAM based DEM refinement are of similar quality. It is thus possible to derive DEMs of high lateral resolution by applying the intensity-based refinement to the less complex SIAM.

Enhanced 3D Shape Recovery Using the Neural-Based Hybrid Reflectance Model

2001 ◽  
Vol 13 (11) ◽  
pp. 2617-2637 ◽  
Author(s):  
Siu-Yeung Cho ◽  
Tommy W. S. Chow
Keyword(s):  
Neural Networks ◽  
Shape Recovery ◽  
Feedforward Neural Networks ◽  
Shape From Shading ◽  
Hybrid Structure ◽  
Radial Basis Function Networks ◽  
Object Shape ◽  
Reflectance Model ◽  
3D Shape Recovery ◽  
Lambertian Model

It is known that most real surfaces usually are neither perfectly Lambertian model nor ideally specular model; rather, they are formed by the hybrid structure of these two models. This hybrid reflectance model still suffers from the noise, strong specular, and unknown reflectivity conditions. In this article, these limitations are addressed, and a new neural-based hybrid reflectance model is proposed. The goal of this method is to optimize a proper reflectance model by learning the weight and parameters of the hybrid structure of feedforward neural networks and radial basis function networks and to recover the 3D object shape by the shape from shading technique with this resulting model. Experimental results, including synthetic and real images, were performed to demonstrate the performance of the proposed reflectance model in the case of different specular effects and noise environments.

scholarly journals REFINEMENT OF STEREO IMAGE ANALYSIS USING PHOTOMETRIC SHAPE RECOVERY AS AN ALTERNATIVE TO BUNDLE ADJUSTMENT

2016 ◽  
Vol XLI-B4 ◽  
pp. 565-572 ◽  
Author(s):  
A. Grumpe ◽  
C. Schröer ◽  
S. Kauffmann ◽  
T. Fricke ◽  
C. Wöhler ◽  
...  
Keyword(s):  
Image Analysis ◽  
Shape Recovery ◽  
Shape From Shading ◽  
Bundle Adjustment ◽  
Stereo Image ◽  
General Interest ◽  
Multiple Images ◽  
Digital Elevation ◽  
High Lateral Resolution ◽  
3D Information

Topographic mapping, e.g. the generation of Digital Elevation Models (DEM), is of general interest to the remote sensing community and scientific research. Commonly, photogrammetric methods, e.g. stereo image analysis methods (SIAM) or bundle adjustment methods (BAM), are applied to derive 3D information based on multiple images of an area. These methods require the detection of control points, i.e. common points within multiple images, which relies on a similarity measure and usually yields a sparse map of 3D points. The full spatial DEM is then obtained by interpolation techniques or imposed restrictions, e.g. smoothness constraints. Since BAM utilizes all images of the area, it is assumed to provide a more accurate DEM than SIAM which utilizes only pairs of images. Intensity-based shape recovery, e.g. shape from shading (SfS), utilizes the reflectance behavior of the object surface and thus provides a dense map of relative height changes, which provide the possibility to refine the photogrammetric DEMs. Based on Rosetta NavCam images of 67P/Churyumov-Gerasimenko we compare intensity-based DEM refinement methods which use DEMs obtained based on SIAM and BAM as a reference. We show that both the SIAM based DEM refinement and the BAM based DEM refinement are of similar quality. It is thus possible to derive DEMs of high lateral resolution by applying the intensity-based refinement to the less complex SIAM.

A neurological dissociation between shape from shading and shape from edges

1996 ◽  
Vol 76 (1-2) ◽  
pp. 117-125 ◽  
Author(s):  
G. Keith Humphrey ◽  
Lawrence A. SymonS ◽  
Andrew M. Herbert ◽  
Melvyn A. Goodale
Keyword(s):  
Shape From Shading
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