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Author(s):  
David Singer ◽  
Dorian Rohner ◽  
Dominik Henrich

AbstractA complete object database containing a model (representing geometric and texture information) of every possible workpiece is a common necessity e.g. for different object recognition or task planning approaches. The generation of these models is often a tedious process. In this paper we present a fully automated approach to tackle this problem by generating complete workpiece models using a robotic manipulator. A workpiece is recorded by a depth sensor from multiple views for one side, then turned, and captured from the other side. The resulting point clouds are merged into one complete model. Additionally, we represent the information provided by the object’s texture using keypoints. We present a proof of concept and evaluate the precision of the final models. In the end we conclude the usefulness of our approach showing a precision of around 1 mm for the resulting models.


2021 ◽  
Vol 3 ◽  
pp. 1-2
Author(s):  
Izabela Gołębiowska ◽  
Tomasz Opach ◽  
Arzu Çöltekin
Keyword(s):  


Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3079
Author(s):  
Sudhakar Sengan ◽  
Ketan Kotecha ◽  
Indragandhi Vairavasundaram ◽  
Priya Velayutham ◽  
Vijayakumar Varadarajan ◽  
...  

Statistical reports say that, from 2011 to 2021, more than 11,915 stray animals, such as cats, dogs, goats, cows, etc., and wild animals were wounded in road accidents. Most of the accidents occurred due to negligence and doziness of drivers. These issues can be handled brilliantly using stray and wild animals-vehicle interaction and the pedestrians’ awareness. This paper briefs a detailed forum on GPU-based embedded systems and ODT real-time applications. ML trains machines to recognize images more accurately than humans. This provides a unique and real-time solution using deep-learning real 3D motion-based YOLOv3 (DL-R-3D-YOLOv3) ODT of images on mobility. Besides, it discovers methods for multiple views of flexible objects using 3D reconstruction, especially for stray and wild animals. Computer vision-based IoT devices are also besieged by this DL-R-3D-YOLOv3 model. It seeks solutions by forecasting image filters to find object properties and semantics for object recognition methods leading to closed-loop ODT.


2021 ◽  
Vol 13 (24) ◽  
pp. 13686
Author(s):  
Marwan Qaid Mohammed ◽  
Lee Chung Kwek ◽  
Shing Chyi Chua ◽  
Abdulaziz Salamah Aljaloud ◽  
Arafat Al-Dhaqm ◽  
...  

In robotic manipulation, object grasping is a basic yet challenging task. Dexterous grasping necessitates intelligent visual observation of the target objects by emphasizing the importance of spatial equivariance to learn the grasping policy. In this paper, two significant challenges associated with robotic grasping in both clutter and occlusion scenarios are addressed. The first challenge is the coordination of push and grasp actions, in which the robot may occasionally fail to disrupt the arrangement of the objects in a well-ordered object scenario. On the other hand, when employed in a randomly cluttered object scenario, the pushing behavior may be less efficient, as many objects are more likely to be pushed out of the workspace. The second challenge is the avoidance of occlusion that occurs when the camera itself is entirely or partially occluded during a grasping action. This paper proposes a multi-view change observation-based approach (MV-COBA) to overcome these two problems. The proposed approach is divided into two parts: 1) using multiple cameras to set up multiple views to address the occlusion issue; and 2) using visual change observation on the basis of the pixel depth difference to address the challenge of coordinating push and grasp actions. According to experimental simulation findings, the proposed approach achieved an average grasp success rate of 83.6%, 86.3%, and 97.8% in the cluttered, well-ordered object, and occlusion scenarios, respectively.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Lei Lei ◽  
Dongen Guo ◽  
Zhihui Feng

This paper proposes a synthetic aperture radar (SAR) image target recognition method using multiple views and inner correlation analysis. Due to the azimuth sensitivity of SAR images, the inner correlation between multiview images participating in recognition is not stable enough. To this end, the proposed method first clusters multiview SAR images based on image correlation and nonlinear correlation information entropy (NCIE) in order to obtain multiple view sets with strong internal correlations. For each view set, the multitask sparse representation is used to reconstruct the SAR images in it to obtain high-precision reconstructions. Finally, the linear weighting method is used to fuse the reconstruction errors from different view sets and the target category is determined according to the fusion error. In the experiment, the tests are conducted based on the MSTAR dataset, and the results validate the effectiveness of the proposed method.


2021 ◽  
Author(s):  
◽  
Marian Evans

<p>This thesis explores whether an analytical practice, combining creative writing with activism and based in academia, can help open space for more women scriptwriters within New Zealand feature filmmaking. It links autoethnography with activist and experience-based methodologies within a creative writing framework that includes a memoir, an essay, a report, diaries and emails, an essay screenplay and weblogging, to present multiple views of an investigation into state investment in women‘s feature filmmaking and the researcher‘s own experience as an activist researcher and apprentice scriptwriter. It concludes that, within an analytical creative writing practice, autoethnography‘s accommodation of a single researcher participant‘s shifting roles may help to open space for women scriptwriters to contribute to New Zealand feature films.</p>


2021 ◽  
Author(s):  
◽  
Marian Evans

<p>This thesis explores whether an analytical practice, combining creative writing with activism and based in academia, can help open space for more women scriptwriters within New Zealand feature filmmaking. It links autoethnography with activist and experience-based methodologies within a creative writing framework that includes a memoir, an essay, a report, diaries and emails, an essay screenplay and weblogging, to present multiple views of an investigation into state investment in women‘s feature filmmaking and the researcher‘s own experience as an activist researcher and apprentice scriptwriter. It concludes that, within an analytical creative writing practice, autoethnography‘s accommodation of a single researcher participant‘s shifting roles may help to open space for women scriptwriters to contribute to New Zealand feature films.</p>


2021 ◽  
Author(s):  
Hassan Noureddine ◽  
Cyril Ray ◽  
Christophe Claramunt

Photonics ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 424
Author(s):  
Evelyn Gutierrez ◽  
Benjamín Castañeda ◽  
Sylvie Treuillet ◽  
Ivan Hernandez

Along with geometric and color indicators, thermography is another valuable source of information for wound monitoring. The interaction of geometry with thermography can provide predictive indicators of wound evolution; however, existing processes are focused on the use of high-cost devices with a static configuration, which restricts the scanning of large surfaces. In this study, we propose the use of commercial devices, such as mobile devices and portable thermography, to integrate information from different wavelengths onto the surface of a 3D model. A handheld acquisition is proposed in which color images are used to create a 3D model by using Structure from Motion (SfM), and thermography is incorporated into the 3D surface through a pose estimation refinement based on optimizing the temperature correlation between multiple views. Thermal and color 3D models were successfully created for six patients with multiple views from a low-cost commercial device. The results show the successful application of the proposed methodology where thermal mapping on 3D models is not limited in the scanning area and can provide consistent information between multiple thermal camera views. Further work will focus on studying the quantitative metrics obtained by the multi-view 3D models created with the proposed methodology.


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