scholarly journals SREVAS: Shading Based Surface Refinement under Varying Albedo and Specularity

2020 ◽  
Vol 12 (21) ◽  
pp. 3488
Author(s):  
Zhihua Hu ◽  
Yaolin Hou ◽  
Pengjie Tao ◽  
Jie Shan
Keyword(s):  
Stereo Vision ◽  
Specular Reflection ◽  
Low Cost ◽  
Shape From Shading ◽  
Specular Reflectance ◽  
Specular Reflections ◽  
New Development ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Surface Refinement

Shape-from-shading and stereo vision are two complementary methods to reconstruct 3D surface from images. Stereo vision can reconstruct the overall shape well but is vulnerable in texture-less and non-Lambertian areas where shape-from-shading can recover fine details. This paper presents a novel, generic shading based method to refine the surface generated by multi-view stereo. Different from most of the shading based surface refinement methods, the new development does not assume the ideal Lambertian reflectance, known illumination, or uniform surface albedo. Instead, specular reflectance is taken into account while the illumination can be arbitrary and the albedo can be non-uniform. Surface refinement is achieved by solving an objective function where the imaging process is modeled with spherical harmonics illumination and specular reflectance. Our experiments are carried out using images of indoor scenes with obvious specular reflection and of outdoor scenes with a mixture of Lambertian and specular reflections. Comparing to surfaces created by current multi-view stereo and shape-from-shading methods, the developed method can recover more fine details with lower omission rates (6.11% vs. 24.25%) in the scenes evaluated. The benefit is more apparent when the images are taken with low-cost, off-the-shelf cameras. It is therefore recommended that a general shading model consisting of varying albedo and specularity shall be used in routine surface reconstruction practice.

scholarly journals Flexible time course of spatial frequency use during scene categorization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sandro L. Wiesmann ◽  
Laurent Caplette ◽  
Verena Willenbockel ◽  
Frédéric Gosselin ◽  
Melissa L.-H. Võ
Keyword(s):  
Time Course ◽  
Task Characteristics ◽  
Scene Categorization ◽  
Fine Grained ◽  
Spatial Frequencies ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Fine Pattern ◽  
Late Stages ◽  
Basic Level

AbstractHuman observers can quickly and accurately categorize scenes. This remarkable ability is related to the usage of information at different spatial frequencies (SFs) following a coarse-to-fine pattern: Low SFs, conveying coarse layout information, are thought to be used earlier than high SFs, representing more fine-grained information. Alternatives to this pattern have rarely been considered. Here, we probed all possible SF usage strategies randomly with high resolution in both the SF and time dimensions at two categorization levels. We show that correct basic-level categorizations of indoor scenes are linked to the sampling of relatively high SFs, whereas correct outdoor scene categorizations are predicted by an early use of high SFs and a later use of low SFs (fine-to-coarse pattern of SF usage). Superordinate-level categorizations (indoor vs. outdoor scenes) rely on lower SFs early on, followed by a shift to higher SFs and a subsequent shift back to lower SFs in late stages. In summary, our results show no consistent pattern of SF usage across tasks and only partially replicate the diagnostic SFs found in previous studies. We therefore propose that SF sampling strategies of observers differ with varying stimulus and task characteristics, thus favouring the notion of flexible SF usage.

Versatile thin layer spectroelectrochemical cell employing specular reflectance

1987 ◽  
Vol 65 (5) ◽  
pp. 919-923 ◽  
Author(s):  
A. Scott Hinman ◽  
Brad J. Pavelich
Keyword(s):  
Thin Layer ◽  
Specular Reflection ◽  
Incident Light ◽  
Tetrabutylammonium Perchlorate ◽  
Specular Reflectance ◽  
Advantages And Disadvantages ◽  
Ftir Characterization ◽  
Sandwich Type

A versatile thin layer spectroelectrochemical cell employing specular reflection of the incident light beam from the electrode surface is described. Its application to in-situ uv–vis and FTIR characterization of the products of electrochemical reactions and to thin layer voltammetry and coulometry as well as conventional cyclic voltammetry is demonstrated for the oxidation of tetraphenylporphinatozinc in dichloroethane/tetrabutylammonium perchlorate solution. The advantages and disadvantages of this type of cell as compared to more conventional sandwich type optically transparent thin layer electrodes are discussed.

scholarly journals 3D Object Detection Using Scale Invariant and Feature Reweighting Networks

2019 ◽  
Vol 33 ◽  
pp. 9267-9274 ◽  
Author(s):  
Xin Zhao ◽  
Zhe Liu ◽  
Ruolan Hu ◽  
Kaiqi Huang
Keyword(s):  
Object Detection ◽  
Network Architecture ◽  
Point Clouds ◽  
Scale Invariant ◽  
3D Object ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Bounding Boxes ◽  
The One ◽  
3D Object Detection

3D object detection plays an important role in a large number of real-world applications. It requires us to estimate the localizations and the orientations of 3D objects in real scenes. In this paper, we present a new network architecture which focuses on utilizing the front view images and frustum point clouds to generate 3D detection results. On the one hand, a PointSIFT module is utilized to improve the performance of 3D segmentation. It can capture the information from different orientations in space and the robustness to different scale shapes. On the other hand, our network obtains the useful features and suppresses the features with less information by a SENet module. This module reweights channel features and estimates the 3D bounding boxes more effectively. Our method is evaluated on both KITTI dataset for outdoor scenes and SUN-RGBD dataset for indoor scenes. The experimental results illustrate that our method achieves better performance than the state-of-the-art methods especially when point clouds are highly sparse.

Design of a New Non-Contact Torque Sensor for Rotating Stepped Shaft by Monitoring Magnetic Field

2010 ◽  
Vol 44-47 ◽  
pp. 547-551 ◽  
Author(s):  
Gang Shi ◽  
Na Wang ◽  
Chong Du Cho
Keyword(s):  
Magnetic Field ◽  
Power Transmission ◽  
Low Cost ◽  
Time Algorithm ◽  
Magnetic Sensors ◽  
Torque Sensor ◽  
Rotating Shaft ◽  
Stepped Shaft ◽  
New Development ◽  
Contact Sensor

In this paper, a new non-contact sensor is presented for detecting torque of a rotating stepped shaft which is frequently employed in power transmission system. This sensor doesn’t require cutting or lengthening the rotating shaft. Torque value is obtained by using two magnetic sensors to sense magnetic field intensity of two permanent rubber magnets fixed at the outer surface of the shaft. The phase difference between these two induction signals is used to determine torque of the stepped shaft. A real-time algorithm based on LabVIEW is employed to obtain the measured torque value. The present work has demonstrated that non-contact torque measurement for rotating stepped shaft by monitoring magnetic field is feasible. It seems like that further development will result in low-cost torque sensor. It is hoped that this kind of sensor can lead to a new development direction of torque sensor for rotating shaft.

Low-cost FPGA stereo vision system for real time disparity maps calculation

2012 ◽  
Vol 36 (4) ◽  
pp. 281-288 ◽  
Author(s):  
Paolo Zicari ◽  
Stefania Perri ◽  
Pasquale Corsonello ◽  
Giuseppe Cocorullo
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Vision System ◽  
Low Cost ◽  
Stereo Vision System ◽  
Disparity Maps

A New Image Irradiance Equation for Perspective Shape from Shading of Hybrid Surfaces

2014 ◽  
Vol 519-520 ◽  
pp. 676-679
Author(s):  
Guo Hui Wang ◽  
Jin Cheng ◽  
Quan Rui Wei
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Diffuse Reflection ◽  
Specular Reflection ◽  
Linear Partial Differential Equation ◽  
Shape From Shading ◽  
Point Light Source ◽  
Imaging Model ◽  
Reflectance Model ◽  
Point Light

Shape from shading (SFS) is a classical and important problem in the domain of computer vision. This paper presents a new image irradiance equation for perspective SFS method to reconstruct the hybrid surfaces that have both diffuse reflection and specular reflection. The hybrid reflectance model composed of a linear combination of Oren-Nayar model and Ward model is used to express the hybrid surfaces. An imaging model incorporating near point light source, perspective camera projection and the hybrid reflectance model is established. Under this model, the image irradiance equation has been derived as a non-linear partial differential equation (PDE). The resulting PDE is associated with a static Hamilton-Jacobi (H-J) equation considering the boundary conditions. Thus, the image irradiance equation of hybrid surfaces can be solved further.

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