scholarly journals A Visual Sensor for Domestic Service Robots

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Muhammad Attamimi ◽  
Takayuki Nagai
Keyword(s):  
Three Dimensional ◽  
Recognition Task ◽  
Detection Algorithm ◽  
Domestic Service ◽  
Service Robots ◽  
Occlusion Detection ◽  
Color Information ◽  
Visual Sensor ◽  
Ccd Cameras ◽  
Object Recognition Task

In this study, we present a visual sensor for domestic service robots, which can capture both color information and three-dimensional information in real time, by calibrating a time of flight camera and two CCD cameras. The problem of occlusions is solved by the proposed occlusion detection algorithm. Since the proposed sensor uses two CCD cameras, missing color information of occluded pixels is compensated by one another. We conduct several evaluations to validate the proposed sensor, including investigation on object recognition task under occluded scenes using the visual sensor. The results revealed the effectiveness of proposed visual sensor.  

scholarly journals Fast Overlap Detection between Hard-Core Colloidal Cuboids and Spheres. The OCSI Algorithm

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 72
Author(s):  
Luca Tonti ◽  
Alessandro Patti
Keyword(s):  
Colloidal Particles ◽  
Dynamic Properties ◽  
Wide Spectrum ◽  
Three Dimensional ◽  
Hard Core ◽  
Detection Algorithm ◽  
Three Dimensional Objects ◽  
Aggregation Behaviour ◽  
Sphere Radius ◽  
User Friendly

Collision between rigid three-dimensional objects is a very common modelling problem in a wide spectrum of scientific disciplines, including Computer Science and Physics. It spans from realistic animation of polyhedral shapes for computer vision to the description of thermodynamic and dynamic properties in simple and complex fluids. For instance, colloidal particles of especially exotic shapes are commonly modelled as hard-core objects, whose collision test is key to correctly determine their phase and aggregation behaviour. In this work, we propose the Oriented Cuboid Sphere Intersection (OCSI) algorithm to detect collisions between prolate or oblate cuboids and spheres. We investigate OCSI’s performance by bench-marking it against a number of algorithms commonly employed in computer graphics and colloidal science: Quick Rejection First (QRI), Quick Rejection Intertwined (QRF) and a vectorized version of the OBB-sphere collision detection algorithm that explicitly uses SIMD Streaming Extension (SSE) intrinsics, here referred to as SSE-intr. We observed that QRI and QRF significantly depend on the specific cuboid anisotropy and sphere radius, while SSE-intr and OCSI maintain their speed independently of the objects’ geometry. While OCSI and SSE-intr, both based on SIMD parallelization, show excellent and very similar performance, the former provides a more accessible coding and user-friendly implementation as it exploits OpenMP directives for automatic vectorization.

scholarly journals Mice deficient in the NAAG synthetase II gene Rimkla are impaired in a novel object recognition task

2021 ◽  
Author(s):  
Ivonne Becker ◽  
Lihua Wang‐Eckhardt ◽  
Julia Lodder‐Gadaczek ◽  
Yong Wang ◽  
Agathe Grünewald ◽  
...  
Keyword(s):  
Object Recognition ◽  
Recognition Task ◽  
Novel Object Recognition ◽  
Novel Object ◽  
Object Recognition Task ◽  
Novel Object Recognition Task

scholarly journals Generation and Annotation of Simulation-Real Ship Images for Convolutional Neural Networks Training and Testing

2021 ◽  
Vol 11 (13) ◽  
pp. 5931
Author(s):  
Ji’an You ◽  
Zhaozheng Hu ◽  
Chao Peng ◽  
Zhiqiang Wang
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Image Annotation ◽  
Three Dimensional ◽  
Image Data ◽  
Detection Algorithm ◽  
Simulation Software ◽  
High Quality ◽  
Annotation Method ◽  
Detection Of Objects

Large amounts of high-quality image data are the basis and premise of the high accuracy detection of objects in the field of convolutional neural networks (CNN). It is challenging to collect various high-quality ship image data based on the marine environment. A novel method based on CNN is proposed to generate a large number of high-quality ship images to address this. We obtained ship images with different perspectives and different sizes by adjusting the ships’ postures and sizes in three-dimensional (3D) simulation software, then 3D ship data were transformed into 2D ship image according to the principle of pinhole imaging. We selected specific experimental scenes as background images, and the target ships of the 2D ship images were superimposed onto the background images to generate “Simulation–Real” ship images (named SRS images hereafter). Additionally, an image annotation method based on SRS images was designed. Finally, the target detection algorithm based on CNN was used to train and test the generated SRS images. The proposed method is suitable for generating a large number of high-quality ship image samples and annotation data of corresponding ship images quickly to significantly improve the accuracy of ship detection. The annotation method proposed is superior to the annotation methods that label images with the image annotation software of Label-me and Label-img in terms of labeling the SRS images.

Three Dimensional Detection of the via in the PCB CT Image Using Morphology Operation

2015 ◽  
Vol 752-753 ◽  
pp. 1406-1412
Author(s):  
Lei Zeng ◽  
Jian Chen ◽  
Han Ning Li ◽  
Bin Yan ◽  
Yi Fu Xu ◽  
...  
Keyword(s):  
Nondestructive Testing ◽  
Printed Circuit Board ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Circuit Board ◽  
Dimensional Structure ◽  
Three Dimension ◽  
Shape Information ◽  
Printed Circuit ◽  
Testing Technology

In modern industry, the nondestructive testing of printed circuit board (PCB) can prevent effectively the system failure and is becoming more and more important. As a vital part of the PCB, the via connects the devices, the components and the wires and plays a very important role for the connection of the circuits. With the development of testing technology, the nondestructive testing of the via extends from two dimension to three dimension in recent years. This paper proposes a three dimensional detection algorithm using morphology method to test the via. The proposed algorithm takes full advantage of the three dimensional structure and shape information of the via. We have used the proposed method to detect via from PCB images with different size and quality, and found the detection performances to be very encouraging.

Moving Objects Detection Algorithm Based on Three-Dimensional Gaussian Mixture Codebook Model Using XYZ Color Model

2013 ◽  
Vol 347-350 ◽  
pp. 3505-3509 ◽  
Author(s):  
Jin Huang ◽  
Wei Dong Jin ◽  
Na Qin
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Moving Objects ◽  
Three Dimensional ◽  
Gaussian Mixture ◽  
Detection Algorithm ◽  
Color Model ◽  
Moving Objects Detection ◽  
Objects Detection ◽  
Model Algorithm

In order to reduce the difficulty of adjusting parameters for the codebook model and the computational complexity of probability distribution for the Gaussian mixture model in intelligent visual surveillance, a moving objects detection algorithm based on three-dimensional Gaussian mixture codebook model using XYZ color model is proposed. In this algorithm, a codebook model based on XYZ color model is built, and then the Gaussian model based on X, Y and Z components in codewords is established respectively. In this way, the characteristic of the three-dimensional Gaussian mixture model for the codebook model is obtained. The experimental results show that the proposed algorithm can attain higher real-time capability and its average frame rate is about 16.7 frames per second, while it is about 8.3 frames per second for the iGMM (improved Gaussian mixture model) algorithm, about 6.1 frames per second for the BM (Bayes model) algorithm, about 12.5 frames per second for the GCBM (Gaussian-based codebook model) algorithm, and about 8.5 frames per second for the CBM (codebook model) algorithm in the comparative experiments. Furthermore the proposed algorithm can obtain better detection quantity.

A novel delayed non-match to sample object recognition task that allows simultaneous in vivo microdialysis

2010 ◽  
Vol 189 (2) ◽  
pp. 210-215 ◽  
Author(s):  
Jouni Ihalainen ◽  
Timo Sarajärvi ◽  
Susanna Kemppainen ◽  
Pekka Keski-Rahkonen ◽  
Marko Lehtonen ◽  
...  
Keyword(s):  
Object Recognition ◽  
Recognition Task ◽  
In Vivo Microdialysis ◽  
Match To Sample ◽  
Object Recognition Task ◽  
Sample Object

An Octree Method for Interference Detection in Computer Aided 3-D Packing

1994 ◽  
Author(s):  
Zuo Dai ◽  
Jianzhong Cha
Keyword(s):  
Real Time ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Time Response ◽  
Interference Detection ◽  
Computer Memory ◽  
Computational Accuracy ◽  
Data Space ◽  
Computer Aided ◽  
Packing Process

Abstract In simulating the three dimensional packing process with arbitrary shaped objects, the task of detecting interference between objects is important and very difficult. This paper, representing the three dimensional packing space and objects with an octree, presents an effective interference detection algorithm, which can overcome the performance shortcomings that the conventional methods have in terms of real-time response, computer memory and computational accuracy. By recording the distribution status of packing space in the “bits” of short integers, the data space can be compressed to 1/16 of that used by conventional algorithms.

scholarly journals On the intermittency of orographic gravity wave hotspots and its importance for middle atmosphere dynamics

2020 ◽  
Author(s):  
Ales Kuchar ◽  
Petr Sacha ◽  
Roland Eichinger ◽  
Christoph Jacobi ◽  
Petr Pisoft ◽  
...  
Keyword(s):  
Climate Model ◽  
Middle Atmosphere ◽  
Model Simulation ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Dynamics Simulation ◽  
Dynamical Structure ◽  
Wave Forcing ◽  
Peak Detection Algorithm ◽  
Opposing Effects

Abstract. When orographic gravity waves (OGWs) break, they dissipate their momentum and energy and thereby influence the thermal and dynamical structure of the atmosphere. This OGW forcing mainly takes place in the middle atmosphere. It is zonally asymmetric and strongly intermittent. So-called OGW hotspot regions have been shown to exert a large impact on the total wave forcing, in particular in the lower stratosphere (LS). Motivated by this we investigate the asymmetrical distribution of the three-dimensional OGW drag (OGWD) for selected hotspot regions in the specified dynamics simulation of the chemistry-climate model CMAM (Canadian Middle Atmosphere Model) for the period 1979–2010. As an evaluation, we first compare zonal mean OGW fluxes and GW drag (GWD) of the model simulation with observations and reanalyses in the northern hemisphere. We find an overestimation of GW momentum fluxes and GWD in the model's LS, presumably attributable to the GW parameterizations which are tuned to correctly represent the dynamics of the southern hemisphere. In the following, we define three hotspot regions which are of particular interest for OGW studies, namely the Himalayas, the Rocky Mountains and East Asia. The GW drags in these hotspot regions emerge as strongly intermittent, a result that can also quantitatively be corroborated with observational studies. Moreover, a peak-detection algorithm is applied to capture the intermittent and zonally asymmetric character of OGWs breaking in the LS and to assess composites for the three hotspot regions. This shows that LS peak OGW events can have opposing effects on the upper stratosphere and mesosphere depending on the hotspot region. Our analysis constitutes a new method for studying the intermittency of OGWs, thereby facilitating a new possibility to assess the effect of particular OGW hotspot regions on middle atmospheric dynamics.

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