Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot Manipulation

6D object pose estimation aims to infer the relative pose between the object and the camera using a single image or multiple images. Most works have focused on predicting the object pose without associated uncertainty under occlusion and structural ambiguity (symmetricity). However, these works demand prior information about shape attributes, and this condition is hardly satisfied in reality; even asymmetric objects may be symmetric under the viewpoint change. In addition, acquiring and fusing diverse sensor data is challenging when extending them to robotics applications. Tackling these limitations, we present an ambiguity-aware 6D object pose estimation network, PrimA6D++, as a generic uncertainty prediction method. The major challenges in pose estimation, such as occlusion and symmetry, can be handled in a generic manner based on the measured ambiguity of the prediction. Specifically, we devise a network to reconstruct the three rotation axis primitive images of a target object and predict the underlying uncertainty along each primitive axis. Leveraging the estimated uncertainty, we then optimize multi-object poses using visual measurements and camera poses by treating it as an object SLAM problem. The proposed method shows a significant performance improvement in T-LESS and YCB-Video datasets. We further demonstrate real-time scene recognition capability for visually-assisted robot manipulation. Our code and supplementary materials are available at https://github.com/rpmsnu/PrimA6D.Comment: IEEE Robotics and Automation Letter

Selective Kernel Attention for Robust Speaker Verification

Recent state-of-the-art speaker verification architectures adopt multi-scale processing and frequency-channel attention techniques. However, their full potential may not have been exploited because these techniques' receptive fields are fixed where most convolutional layers operate with specified kernel sizes such as 1, 3 or 5. We aim to further improve this line of research by introducing a selective kernel attention (SKA) mechanism. The SKA mechanism allows each convolutional layer to adaptively select the kernel size in a data-driven fashion based on an attention mechanism that exploits both frequency and channel domain using the previous layer's output. We propose three module variants using the SKA mechanism whereby two modules are applied in front of an ECAPA-TDNN model, and the other is combined with the Res2Net backbone block. Experimental results demonstrate that our proposed model consistently outperforms the conventional counterpart on the three different evaluation protocols in terms of both equal error rate and minimum detection cost function. In addition, we present a detailed analysis that helps understand how the SKA module works.Comment: Submitted to INTERSPEECH 2022. 5 pages, 3 figures, 1 tabl

Development and characterization of nine polymorphic microsatellite markers in the seven-spotted lady beetle, Coccinella septempunctata (Coleoptera: Coccinellidae)

In this study, nine microsatellite loci were isolated and characterized from the seven-spotted lady beetle, Coccinella septempunctata (Coleoptera: Coccinellidae). The loci were validated and characterized using 20 samples collected from five Korean localities. These results indicate that some loci were highly variable in terms of number of alleles (2 to 13), heterozygosity (0.10 to 0.40), and polymorphic information content (0.31 to 0.85). These microsatellite markers will be very valuable for population genetic studies of C. septempunctata.Key words: Seven-spotted lady beetle, Coccinella septempunctata, microsatellite Deoxyribonucleic acid (DNA)

Design of exceptionally strong and conductive Cu alloys beyond the conventional speculation via the interfacial energy-controlled dispersion of gamma-Al2O3 nanoparticles

The development of Cu-based alloys with high-mechanical properties (strength, ductility) and electrical conductivity plays a key role over a wide range of industrial applications. Successful design of the materials, however, has been rare due to the improvement of mutually exclusive properties as conventionally speculated. In this paper, we demonstrate that these contradictory material properties can be improved simultaneously if the interfacial energies of heterogeneous interfaces are carefully controlled. We uniformly disperse γ-Al2O3 nanoparticles over Cu matrix, and then we controlled atomic level morphology of the interface γ-Al2O3 //Cu by adding Ti solutes. It is shown that the Ti dramatically drives the interfacial phase transformation from very irregular to homogeneous spherical morphologies resulting in substantial enhancement of the mechanical property of Cu matrix. Furthermore, the Ti removes impurities (O and Al) in the Cu matrix by forming oxides leading to recovery of the electrical conductivity of pure Cu. We validate experimental results using TEM and EDX combined with first-principles density functional theory (DFT) calculations, which all consistently poise that our materials are suitable for industrial applications.1

Association between cardiorespiratory fitness and the prevalence of metabolic syndrome among Korean adults: a cross sectional study

BACKGROUND: The purpose of the current study was to investigate the association between cardiorespiratory fitness (CRF), measured by a simple step test, and the prevalence of metabolic syndrome among Korean adults, in a cross sectional design. METHODS: A total of 1,007 Korean adults (488 men and 519 women) who underwent routine health checkups were recruited. CRF was measured by Tecumseh step test. The National Cholesterol Education Program’s Adult Treatment Panel III guideline was used to determine the prevalence of metabolic syndrome. A logistic regression was performed to reveal possible associations. RESULTS: The results of the study showed that a lower level of CRF was significantly associated with a higher prevalence of metabolic syndrome in men, but not in women. On the other hand, higher BMI was associated with a higher prevalence of metabolic syndrome in both men and women. However, BMI was not associated with fasting glucose nor hemoglobinA1c in men. When the combined impact of BMI and CRF on the prevalence of metabolic syndrome was analyzed, a significantly increased prevalence of metabolic syndrome was found in both men (odds ratio [OR]: 18.8, 95% Confidence Interval [CI]: 5.0 - 70.5) and women (OR: 8.1, 95% CI: 2.8 - 23.9) who had high BMI and low cardiorespiratory fitness. On the other hand, the prevalence of metabolic syndrome was only increased 7.9 times (95% CI: 2.0 - 31.2) in men and 5.4 times (95% CI: 1.9 - 15.9) in women who had high level of CRF and high BMI. CONCLUSION: In conclusion, the current study demonstrated the low CRF and obesity was a predictor for metabolic syndrome in Korean adults

OCT using spectrally resolved bandwidth

An apparatus is disclosed for studying an object based on at least one of polarization, space, position or angle of light that has reflected from the object. An optical tomographic instrumentation of the apparatus includes a light source coupled to a source path, a sample path, a reference path, and a detection path, wherein the light source generates a spectrally resolved bandwidth. The spectrally resolved bandwidth includes a plurality of spectrally resolved cells and a detector in the detection path for analyzing light reflected from an object in the sample path and the light reflected in the reference path based upon at least one of the polarization, spatial relationship, position or angle domains.Board of Regents, University of Texas Syste