Reviewerly/exHarmony huggingface dataset:
Joint Analysis and Segmentation of Time-Varying Data with Outliers

Authors:
raw_author_name: Stefania Colonnese
raw_affiliation_string: Sapienza University of Rome, Rome, Italy
raw_author_name: Gaetano Scarano
raw_affiliation_string: Sapienza University of Rome, Rome, Italy
raw_author_name: Panos P. Markopoulos
raw_affiliation_string: The University of Texas at San Antonio, San Antonio, TX, 78249, USA
raw_author_name: Dimitris A. Pados
raw_affiliation_string: Florida Atlantic University, Boca Raton, FL 33431, USA

Abstract: Principal-Component Analysis (PCA) is a fundamental tool in data science and machine learning, used for compressing, analyzing, visualizing, and processing large datasets. At the same time, temporal segmentation is important for coherent component analysis of big data collections generated by time-varying distributions. However, both segmentation and PCA can be critically affected and misled by corrupted points that often exist in big data collections. To address these issues, we propose a novel and robust method for joint segmentation and principal-component analysis of time-varying data, based on L1-norm formulations. Our proposed method estimates robust L1-norm principal components (L1-PCs) over different temporal horizons and combines them to perform outlier detection, data segmentation, and subspace estimation. Numerical studies on real-world data, including videos and smartphone-sensed human body motion measurements, corroborate the merits of the proposed method in terms of segmentation, PCA, and outlier detection/removal.
A multi-objective evolutionary algorithm based on dimension exploration and discrepancy evolution for UAV path planning problem

Authors:
raw_author_name: Chengyu Xie
raw_affiliation_string: School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China
raw_author_name: Zongfu Luo
raw_affiliation_string: School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China
raw_author_name: Chuanfu Zhang
raw_affiliation_string: School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China
raw_author_name: Tao Zhang
raw_affiliation_string: School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou, 510275, China

Abstract: Path planning is a crucial process for unmanned aerial vehicles (UAVs) and involves finding a path that is both short and safe. However, with the ever-increasing complexity of the environment, solving the UAV path-planning problem is challenging. Traditional path-planning methods cannot handle conflicting goals effectively, and existing objective methods lack targeted exploration mechanisms, resulting in unsatisfactory outcomes. By modeling the UAV path-planning problem via multi-objective optimization, this study designed a reasonable objective function composition for the model and considered obstacle avoidance as a hard constraint to satisfy the actual situation. A multi-objective evolutionary algorithm based on dimensional exploration and discrepancy evolution (MOEA-2DE) is presented. In particular, MOEA-2DE utilizes dimensional perturbation to identify key dimensions to facilitate prior exploration and enhance the targeted search. An adaptive evolution strategy based on population discrepancy was employed to assess the evolution process, and various methods were adopted to balance convergence and diversity. The effectiveness of the MOEA-2DE was demonstrated through the design of two intricate terrain sets and comparisons with various classic and state-of-the-art multi-objective evolutionary algorithms (MOEAs), including those designed for UAV path planning across multiple metrics. The results verify the superiority of MOEA-2DE in terms of both convergence speed and final effect.
A comparative study of Augmented Reality rendering techniques for industrial assembly inspection

Authors:
raw_author_name: Santina Fortuna
raw_affiliation_string: Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, P. Bucci, 46C, 87036 Rende, CS, Italy
raw_author_name: Loris Barbieri
raw_affiliation_string: Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, P. Bucci, 46C, 87036 Rende, CS, Italy
raw_author_name: Emanuele Marino
raw_affiliation_string: Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, P. Bucci, 46C, 87036 Rende, CS, Italy
raw_author_name: Fabio Bruno
raw_affiliation_string: Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria, P. Bucci, 46C, 87036 Rende, CS, Italy

Abstract: In the manufacturing industry, Augmented Reality (AR) has shown significant potential in enhancing operators’ capabilities while performing inspection and assembly activities. However, the augmented visualization of virtual models on physical components can present challenges and potential misunderstandings, as the visualization mode greatly influences the perception of components and the amount of information received. This study investigates the impact of rendering techniques on user performance during industrial assembly inspection tasks. In particular, a set of rendering techniques, suitable for industrial AR applications, have been selected and implemented through a dedicated AR tool. The selected AR rendering techniques have been compared, in terms of qualitative and quantitative metrics, in order to test their efficiency and effectiveness for industrial assembly inspection activities. 17 domain experts and 33 representative users have been involved in the experimental study which outcomes reveal that the rendering techniques play a significant role in assisting operators for identifying design discrepancies in industrial products. Furthermore, a correlation has been observed between the two AR rendering techniques best suited to support industrial inspection activities and the types of assembly errors detected.
Counting roots of fully triangular polynomials over finite fields

Authors:
raw_author_name: José Gustavo Coelho
raw_author_name: Fabio Enrique Brochero Martínez

Abstract: Let Fq be a finite field with q elements, f∈Fq[x1,…,xn] a polynomial in n variables and let us denote by N(f) the number of roots of f in Fqn. In this paper we consider the family of fully triangular polynomials, i.e., polynomials of the formf(x1,…,xn)=a1x1d1,1+a2x1d1,2x2d2,2+…+anx1d1,n⋯xndn,n−b, where di,j>0 for all 1≤i≤j≤n. For these polynomials, we obtain explicit formulas for N(f) when the augmented degree matrix of f is row-equivalent to the augmented degree matrix of a linear polynomial or a quadratic diagonal polynomial.
Development of a novel multi-line laser triangulation scanning system based on the rotary diffraction grating

Authors:
raw_author_name: Yao Wang
raw_affiliation_string: Zhejiang University, State Key Laboratory of Modern Optical Instrumentation, CNERC for Optical Instruments, 38 Zheda Road, Xihu District, Hangzhou 310027, China
raw_author_name: Peng Zhou
raw_affiliation_string: Zhejiang University, State Key Laboratory of Modern Optical Instrumentation, CNERC for Optical Instruments, 38 Zheda Road, Xihu District, Hangzhou 310027, China
raw_author_name: Chuan-Wei Yao
raw_affiliation_string: Zhejiang University, State Key Laboratory of Modern Optical Instrumentation, CNERC for Optical Instruments, 38 Zheda Road, Xihu District, Hangzhou 310027, China
raw_author_name: Heng-Yu Wang
raw_affiliation_string: Zhejiang University, State Key Laboratory of Modern Optical Instrumentation, CNERC for Optical Instruments, 38 Zheda Road, Xihu District, Hangzhou 310027, China
raw_author_name: Bin Lin
raw_affiliation_string: Research Institute of Zhejiang University-Taizhou, No. 618, Shifu Avenue West Section, Jiaojiang District, Taizhou 318000, China; Zhejiang University, State Key Laboratory of Modern Optical Instrumentation, CNERC for Optical Instruments, 38 Zheda Road, Xihu District, Hangzhou 310027, China

Abstract: The laser triangulation scanning system (LTSS) is widely employed in three-dimensional (3D) measurement fields owing to its high measurement accuracy. However, due to the limitations of the exploited motion, the traditional LTSS fails to be satisfactory for certain precise and efficient industrial applications. In this paper, a new multi-line laser triangulation scanning system (MLTSS) via integrating a rotary diffraction grating was proposed to address this problem. The image sequence of the divergent laser lines with variable angles on the object can be captured as the grating rotates. This enables to obtain the multiple profiles simultaneously during one frame. A novel method to distinguish laser lines in a single frame which enhances the measurement range was described. The measurement principle and workflow of the proposed system are explained in detail. The calibration algorithm of light planes of the proposed system utilizing the equivalent grating equation is simplified compared to the traditional algorithm. The developed setup and the measured object remain stationary throughout the whole scanning, which relieves the mechanical error caused by the motion. Moreover, the utilized grating facilitates to miniaturize the device. The experiments demonstrate the validity of the proposed system.
Design optimization of a hexapod vibration isolation system for electro-optical payload

Authors:
raw_author_name: Weipeng LI
raw_affiliation_string: School of Astronautics, Beihang University, Beijing 100191, China
raw_author_name: Xiaoyan ZHANG
raw_affiliation_string: School of Astronautics, Beihang University, Beijing 100191, China

Abstract: The electro-optical payloads on mobile platforms generally suffer undesirable vibrations generated by maneuvers and turbulence. These vibrations are in six degrees of freedom and cause line-of-sight jitters, resulting in image blurring and loss of tracking accuracy. In this paper, a Hexapod Vibration Isolation System (HVIS) is proposed and optimized to solve this problem. The optimization aims to centralize and minimize the natural frequencies of HVIS, for expanding the vibration isolation bandwidth and improving the vibration isolation in the higher frequency band. Considering that the design space for HVIS is limited and interfered with the frames of the mobile platform, a non-collision algorithm is proposed and applied in the optimization to obtain the feasible optimal design. The optimization result shows that the natural frequency bandwidth has been reduced by 42.9%, and the maximum natural frequency is reduced by 30.2%. The prototypes of initial and optimal designs are manufactured and tested. Both simulated and experimental results demonstrate the validity of the optimization, and the optimal design provides a maximum of 15 dB more isolation in rotation direction than the initial design.
Deep generative network for image inpainting with gradient semantics and spatial-smooth attention

Authors:
raw_author_name: Ziqi Sheng
raw_affiliation_string: School of Computer Science and Engineering, Guangdong Province Key Laboratory of Information Security Technology, Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou 510006, China
raw_author_name: Wenbo Xu
raw_affiliation_string: School of Computer Science and Engineering, Guangdong Province Key Laboratory of Information Security Technology, Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou 510006, China
raw_author_name: Cong Lin
raw_affiliation_string: Applied Laboratory of Dig Data and Education Statistics, School of Statistics and Mathematics, Guangdong University of Finance and Economics, Guangzhou 510320, China
raw_author_name: Wei Lu
raw_affiliation_string: School of Computer Science and Engineering, Guangdong Province Key Laboratory of Information Security Technology, Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou 510006, China
raw_author_name: Long Ye
raw_affiliation_string: State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing 100024, China

Abstract: As a powerful forgery operation in the image content security area, image inpainting based on deep generative networks can yield visually appealing outputs but often produces ambiguous artifacts, especially in boundary and high semantic areas. To address this issue, a novel end-to-end network with gradient semantics and spatial-smooth attention (GS-SSA) is proposed, which combines a gradient learning network and an image inpainting network. The gradient learning network is meant to properly anticipate the gradient semantics in the hole region and get a complete gradient semantic map. The image inpainting network utilizes the complete gradient semantic map to better repair the missing pixels and obtain the final inpainting results. Moreover, spatial-smooth attention is introduced into the image inpainting network, considering both the spatial structural relations and the surrounding information in the hole region. Experimental results on public datasets show the superiority of the proposed method, especially in large-hole region tasks.
STSIC: Swin-transformer-based scalable image coding for human and machine

Authors:
raw_author_name: Shipei Wang
raw_affiliation_string: Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Science, Shanghai University, Shanghai 200444, China
raw_author_name: Ping An
raw_affiliation_string: Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Science, Shanghai University, Shanghai 200444, China
raw_author_name: Chao Yang
raw_affiliation_string: Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Science, Shanghai University, Shanghai 200444, China
raw_author_name: Kunqiang Huang
raw_affiliation_string: Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Science, Shanghai University, Shanghai 200444, China
raw_author_name: Xinpeng Huang
raw_affiliation_string: Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Science, Shanghai University, Shanghai 200444, China

Abstract: Recently, as the visual data captured by smart terminal devices is mainly served for machine analysis, e.g., image classification, object detection, and sometimes also for human viewing in special scenarios, a new compression framework should be proposed to meet this demand. In this work, an image coding framework for machine analysis and human viewing simultaneously is proposed, termed STSIC. In order to leverage the relationship between the two tasks, STSIC is built upon a scalable structure, comprising a base layer for machine analysis and image preview at low quality, as well as an enhancement layer for high-quality image reconstruction. More specifically, features are extracted through the backbone and transmitted to the cloud side for tasks on the base layer. Different from the vast majority of existing works, we try to employ the Swin-Transformer as the backbone instead of a convolutional neural network (CNN). Additionally, due to the hierarchical structure of the Swin-Transformer, a feature fusion strategy is applied to generate a common feature that is more friendly to both human and machine tasks. The enhancement layer transfers the residuals between the original images and the reconstructed images from the base layer, thereby improving the quality of image reconstruction for human viewing. The experimental results show that STSIC outperforms relevant benchmarks on object detection, especially under low bitrates. As for image reconstruction, the advantage is weakened, but it still surpasses HEVC on the rate-distortion performance.
Depth as attention to learn image representations for visual localization, using monocular images

Authors:
raw_author_name: Dulmini Hettiarachchi
raw_affiliation_string: Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo 113-0033, Japan
raw_author_name: Ye Tian
raw_affiliation_string: Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo 113-0033, Japan
raw_author_name: Han Yu
raw_affiliation_string: Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-0033, Japan

Abstract: Image retrieval algorithms are widely used in visual localization tasks. In visual localization, we can benefit from retrieving the images depicting same landmark taken from a pose similar to the query. However, state-of-the-art image retrieval algorithms are optimized mainly for landmark retrieval, and do not take camera pose into account. To address this limitation, we propose novel Depth Attention Network (DeAttNet). DeAttNet leverages both visual and depth information in learning a global image representation. Depth varies for similar features captured from different camera poses. Based on this insight, we employ depth within an attention mechanism to discern and emphasize the salient regions. In our method, we utilize monocular depth estimation algorithms to render depth maps. Compared to RGB only image descriptors, significant improvements are obtained with the proposed method on Mapillary Street Level Sequences, Pittsburgh and Cambridge Landmark datasets.
Octagonal lattice-based triangulated shape descriptor engaging second-order derivatives supplementing image retrieval

Authors:
raw_author_name: M. Kanimozhi
raw_affiliation_string: School of Electronics Engineering, VIT, Vellore, India
raw_author_name: M.S. Sudhakar
raw_affiliation_string: School of Electronics Engineering, VIT, Vellore, India

Abstract: Erstwhile shape description schemes lack primarily in establishing trade-offs with accuracy and computational load. Accordingly, a lightweight shape descriptor offering precise definition and compaction of high-frequency features is contributed in this paper using a simple geometrical shape for localization and shape characterization. Initially, the input image is octagonally tessellated and triangularly decomposed into sub-regions whose side-wise differences are evaluated and subjected to second-order differentiation to produce three high-frequency values representing triangle corners. The resultant is processed by the law of sines to yield localized shape features exhibiting congruence and is reiterated on the residual regions, followed by a novel octal encoding scheme encompassing maximal variations in the localized regions. The resulting features are globally fabricated into shape histograms in a non-overlapping manner representing the shape vector. This scheme validated on widely popular benchmark shape datasets demonstrates superior retrieval and recognition accuracies greater than 93% which is lacking in its competitors.
Atmospheric dependence of the direct, diffuse, and global clear-sky conversion ratios between solar photosynthetic active irradiance and photon flux

Authors:
raw_author_name: A. Monetta
raw_affiliation_string: Laboratorio de Energía Solar, Departamento de Física del Litoral, CENUR Litoral Norte, UDELAR, Av. L. Batlle Berres km 508, 50000, Salto, Uruguay
raw_author_name: R. Alonso-Suárez
raw_affiliation_string: Laboratorio de Energía Solar, Departamento de Física del Litoral, CENUR Litoral Norte, UDELAR, Av. L. Batlle Berres km 508, 50000, Salto, Uruguay; Laboratorio de Energía Solar, Instituto de Física, Facultad de Ingeniería, UDELAR, J. Herrera y Reissig 565, 11300, Montevideo, Uruguay
raw_author_name: G. Abal
raw_affiliation_string: Laboratorio de Energía Solar, Departamento de Física del Litoral, CENUR Litoral Norte, UDELAR, Av. L. Batlle Berres km 508, 50000, Salto, Uruguay; Laboratorio de Energía Solar, Instituto de Física, Facultad de Ingeniería, UDELAR, J. Herrera y Reissig 565, 11300, Montevideo, Uruguay

Abstract: The ratio of the global solar photosynthetic active radiation (PAR) photon flux (in μmol/m2s) to global solar PAR irradiance (in W/m2) is of interest to convert one into another. This ratio is usually considered as a constant value close to its extraterrestrial value, 4.55μmol/J. However, this ratio depends on the spectral composition of solar radiation at ground level and it is different for the diffuse and beam components of solar irradiance. Under clear-sky conditions, the three PAR ratios (global, beam and diffuse) are determined by the local atmospheric composition and the relative air mass. In this work, the SMARTS spectral irradiance model with MERRA-2 atmospheric inputs is used to evaluate the dependence of these ratios under clear-sky conditions with air mass, aerosol optical depth (AOD), precipitable water vapor and ozone column. The accuracy of the SMARTS beam spectral irradiance is previously assessed using local spectroradiometer measurements. The clear-sky ratios for the diffuse and direct components increase with increasing air mass, while the global ratio shows only a weak air mass dependence. The clear-sky ratios can be modeled with simple bi-variate linear models in air mass and AOD. These results can be used in similar climatic regions to convert PAR flux to PAR irradiance and vice versa with increased accuracy for the global, direct, and diffuse radiation under cloud-free conditions.
Modeling and Assessing Hip-Knee Joint Coordination Based on Cyclograms Using a Portable Motion Capture System

Authors:
raw_author_name: Liang Peng
raw_affiliation_string: School of Automation, Beijing Institute of Technology, Beijing, China
raw_author_name: Xiwei Peng
raw_affiliation_string: School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
raw_author_name: Zeng-Guang Hou
raw_affiliation_string: Faculty of Innovation Engineering, CAS-MUST Joint Laboratory of Intelligence Science and Technology, Macau University of Science and Technology, Macau, China
raw_author_name: Zejia He
raw_affiliation_string: China Rehabilitation Research Center, Beijing Bo&#x2019;ai Hospital, Beijing, China

Abstract: Cyclograms are useful for describing interjoint coordination in clinical gait analyses. In this paper, we establish a model for generating hip-knee cyclograms at different walking speeds by using B-Spline curves, which could provide reference standards for evaluating hip-knee joint coordination. We use the shape similarity between individual and reference cyclograms to develop a hip-knee joint coordination assessment metric: the dynamic time warping-shape context (DTW-SC). The DTW algorithm is used to match corresponding points between the hip-knee cyclograms, and the matched results are visualized to show abnormal changes in gait patterns. The distance between corresponding points is determined through shape context descriptors and applied to quantify the hip-knee joint coordination of the subjects. To verify the effectiveness of the proposed approach, a stereo vision-based portable lower limb motion capture system is developed to collect hip and knee joint angle data from five healthy and five hemiplegic subjects walking at comfortable speeds. Experimental results show that the range of the modeling error is [0.84°, 2.76°]. DTW-SC metric can visualize and quantify the abnormal patterns of the subject’s hip-knee joint coordination. The work is meaningful in evaluating the hip-knee joint coordination of hemiplegic patients.