6,610 research outputs found
On Recognizing Transparent Objects in Domestic Environments Using Fusion of Multiple Sensor Modalities
Current object recognition methods fail on object sets that include both
diffuse, reflective and transparent materials, although they are very common in
domestic scenarios. We show that a combination of cues from multiple sensor
modalities, including specular reflectance and unavailable depth information,
allows us to capture a larger subset of household objects by extending a state
of the art object recognition method. This leads to a significant increase in
robustness of recognition over a larger set of commonly used objects.Comment: 12 page
Three-dimensional scanning of specular and diffuse metallic surfaces using an infrared technique
For the past two decades, the need for three-dimensional (3-D) scanning of industrial objects has increased significantly and many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non-cooperative surfaces, such as transparent or specular surfaces. To address highly reflective metallic surfaces, we propose the extension of a technique that was originally dedicated to glass objects. In contrast to conventional active triangulation techniques that measure the reflection of visible radiation, we measure the thermal emission of a surface, which is locally heated by a laser source. Considering the thermophysical properties of metals, we present a simulation model of heat exchanges that are induced by the process, helping to demonstrate its feasibility on specular metallic surfaces and predicting the settings of the system. With our experimental device, we have validated the theoretical modeling and computed some 3-D point clouds from specular surfaces of various geometries. Furthermore, a comparison of our results with those of a conventional system on specular and diffuse parts will highlight that the accuracy of the measurement no longer depends on the roughness of the surface
The Use of Separated Reflection Components in Estimating Geometrical Parameters of Curved Surface Elements
Iterative least-squares estimation, requires accurate reflectance models to retrieve geometrical parameters of curved surface elements from an image projection. We investigate the use of separating the diffuse (body) reflection from the specular (surface) reflection being responsible for image highlights. Experiments show that the (smooth) diffuse component yields the best convergence properties, while the (sharp) specular component can contribute to the improvement of the noise insensitivit
Photometric stereo for strong specular highlights
Photometric stereo (PS) is a fundamental technique in computer vision known
to produce 3-D shape with high accuracy. The setting of PS is defined by using
several input images of a static scene taken from one and the same camera
position but under varying illumination. The vast majority of studies in this
3-D reconstruction method assume orthographic projection for the camera model.
In addition, they mainly consider the Lambertian reflectance model as the way
that light scatters at surfaces. So, providing reliable PS results from real
world objects still remains a challenging task. We address 3-D reconstruction
by PS using a more realistic set of assumptions combining for the first time
the complete Blinn-Phong reflectance model and perspective projection. To this
end, we will compare two different methods of incorporating the perspective
projection into our model. Experiments are performed on both synthetic and real
world images. Note that our real-world experiments do not benefit from
laboratory conditions. The results show the high potential of our method even
for complex real world applications such as medical endoscopy images which may
include high amounts of specular highlights
Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions
Purpose:
Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to perform delicate procedures on a beating heart, avoiding the complications of cardiac arrest. This advantage comes with the price of having to deal with a dynamic target which presents technical challenges for the surgical system. In this work, we propose a solution for cardiac motion estimation.
Methods:
Our estimation approach uses a variational framework that guarantees preservation of the complex anatomy of the heart. An advantage of our approach is that it takes into account different disturbances, such as specular reflections and occlusion events. This is achieved by performing a preprocessing step that eliminates the specular highlights and a predicting step, based on a conditional restricted Boltzmann machine, that recovers missing information caused by partial occlusions.
Results:
We carried out exhaustive experimentations on two datasets, one from a phantom and the other from an in vivo procedure. The results show that our visual approach reaches an average minima in the order of magnitude of 10-7 while preserving the heart’s anatomical structure and providing stable values for the Jacobian determinant ranging from 0.917 to 1.015. We also show that our specular elimination approach reaches an accuracy of 99% compared to a ground truth. In terms of prediction, our approach compared favorably against two well-known predictors, NARX and EKF, giving the lowest average RMSE of 0.071.
Conclusion:
Our approach avoids the risks of using mechanical stabilizers and can also be effective for acquiring the motion of organs other than the heart, such as the lung or other deformable objects.Peer ReviewedPostprint (published version
AirCode: Unobtrusive Physical Tags for Digital Fabrication
We present AirCode, a technique that allows the user to tag physically
fabricated objects with given information. An AirCode tag consists of a group
of carefully designed air pockets placed beneath the object surface. These air
pockets are easily produced during the fabrication process of the object,
without any additional material or postprocessing. Meanwhile, the air pockets
affect only the scattering light transport under the surface, and thus are hard
to notice to our naked eyes. But, by using a computational imaging method, the
tags become detectable. We present a tool that automates the design of air
pockets for the user to encode information. AirCode system also allows the user
to retrieve the information from captured images via a robust decoding
algorithm. We demonstrate our tagging technique with applications for metadata
embedding, robotic grasping, as well as conveying object affordances.Comment: ACM UIST 2017 Technical Paper
- …