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8th International conference on Computer Science and Engineering, UBMK 2023

作者： Kalizhanova, Aliya Kunelbayev, Murat Kozbakova, Ainur Aitkulov, Zhalau Malikova, Feruza Zhilkishbayeva, Zulfiya Almaty University of Power Engineering and Telecommunications Named after Gumarbek Daukeyev Institute of Information and Computational Technologies Cs Mshe Rk Almaty Kazakhstan Al-Farabi Kazakh National University Institute of Information and Computational Technologies Cs Mshe Rk Almaty Kazakhstan Almaty Technological University Institute of Information and Computational Technologies Cs Mshe Rk Almaty Kazakhstan Kazakh National Women's Teacher Training University Institute of Information and Computational Technologies Cs Mshe Rk Academic of Logistic and Transport. Almaty Kazakhstan Almaty Technological University Almaty Kazakhstan

ISBN: (纸本)9798350340815

The article examines the modeling and design of a subsystem of fiber-optic sensors for the diagnosis and monitoring of the operability of mechanical structures in a differential system. In this study, the definition of the problem was developed by a mathematical model of the FBG using the transfer matrix method and using this method, a simulation model for the sensor was solved. The transfer matrix method makes it possible to assign spectral characteristics of optical components based on the theory of coupled modes and the matrix description of an electromagnetic wave passing through an optical fiber. The simulation is performed by solving the equations of coupled modes in MatLab (Simulink) using the transfer matrix method, which provides the basis for the relationship between the controlled modes. The method can take into account refractive index profiles of arbitrary shape and be implemented in a tool called MatLab (Simulink). As a result of the study, optimization was carried out, where light is shed on the effectiveness of the proposed scheme for analyzing deformation measurements, obtaining a linear response. It's inventory-friendly, fast, and open-source. The main contribution of the study is the developed simulation model of the subsystem for fiber Bragg sensors, which shows that the power of the side lobes is completely minimized in the Gaussian reflection spectra of FBG, and the results of MatLab (Simulink) are in excellent agreement with the results of the optical lattice. MatLab (Simulink) has a wide range of applications in modeling various optical fibers for various fields such as visualization, communication, material processing and remote sensing. © 2023 IEEE.

关键词： Simulink

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Focus and Adjust: Progressive Refinement Network for Human Object Interaction Detection 26

Focus and Adjust: Progressive Refinement Network for Human O...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Yang, Baixiang Gao, Wei Li, Ge Peking Univ Sch Elect & Comp Engn Beijing Peoples R China Peng Cheng Lab Shenzhen Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Many recent works model the Human Object Interaction detection process as a set prediction problem with the help of transformer architecture while demonstrating promising performance. However, previous transformer-based detectors suffer from the variable scale of instances involved in HOI. Moreover, the naive transformer provides a global receptive field for the query to search for contextual information, which also introduces potential redundant information for the corresponding human-object pair. In this paper, we propose PR-Net, a Progressive Refinement Network equipped with two designed refinement modules to tackle the problems above, which provides a coarse-to-fine framework for Human Object Interaction detection. In addition, the refinement modules are organized in a localization-interaction mutual-guided manner to exploit the benefits of the co-optimization between the instance localization and interaction classification and promote HOI detection performance. Our proposed method achieves competitive performance in two HOI detection benchmarks and extensive experiments demonstrate its effectiveness.

关键词： Location awareness visualization Semantics Detectors Predictive models Benchmark testing Transformers

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The Design and Implementation of Religious Affairs Management information System Based on WebGIS 3

The Design and Implementation of Religious Affairs Managemen...

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3rd International conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Zhang, Chen Sichuan University ChengduSichuan Province China

ISBN: (纸本)9781450385046

As a work of information visualization, this thesis mainly combines information management with digital map services, tentatively structured the bridge between digital theory and anthropological theory, combined with the needs and characteristics of local religious affairs GIS applications, and established SQL Server+ArcSDE spatial database, using WebGIS technology and .NET as the development platform, integrates the spatial database with the attribute database, and realizes the functions of data entry, graphics visualization, query statistics, multi-dimensional topic management, and classified topics. © 2021 ACM.

关键词： information systems

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Monocular Depth Estimation Using Cues Inspired by Biological Vision Systems 26

Monocular Depth Estimation Using Cues Inspired by Biological...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Auty, Dylan Mikolajczyk, Krystian Grp, MatchLab Imperial Coll London Elect & Elect Engn Dept London England

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Monocular depth estimation (MDE) aims to transform an RGB image of a scene into a pixelwise depth map from the same camera view. It is fundamentally ill-posed due to missing information: any single image can have been taken from many possible 3D scenes. Part of the MDE task is, therefore, to learn which visual cues in the image can be used for depth estimation, and how. With training data limited by cost of annotation or network capacity limited by computational power, this is challenging. In this work we demonstrate that explicitly injecting visual cue information into the model is beneficial for depth estimation. Following research into biological vision systems, we focus on semantic information and prior knowledge of object sizes and their relations, to emulate the biological cues of relative size, familiar size, and absolute size. We use state-of-the-art semantic and instance segmentation models to provide external information, and exploit language embeddings to encode relational information between classes. We also provide a prior on the average real-world size of objects. This external information overcomes the limitation in data availability, and ensures that the limited capacity of a given network is focused on known-helpful cues, therefore improving performance. We experimentally validate our hypothesis and evaluate the proposed model on the widely used NYUD2 indoor depth estimation benchmark. The results show improvements in depth prediction when the semantic information, size prior and instance size are explicitly provided along with the RGB images, and our method can be easily adapted to any depth estimation system.

关键词： visualization Three-dimensional displays Machine vision Biological system modeling Semantics Estimation Training data

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Multi-view Based 3D Point Cloud Completion Algorithm for Vehicles 26

Multi-view Based 3D Point Cloud Completion Algorithm for Veh...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Ibrahim, Yahya Nagy, Balazs Benedek, Csaba Peter Pazmany Catholic Univ Fac Informat Technol & Bion Budapest Hungary Inst Comp Sci & Control SZTAKI Budapest Hungary

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

3D vehicle shape completion is a key task in urban environment reconstruction, since the available sensors and 3D scanning procedures (such as Mobile Laser Scanning) in an outdoor city scene cannot usually extract the entire car shapes, which can be necessary for specifying their geometric properties for further analysis or realistic visualization. In this paper, we propose a novel multi-view based 3D object point cloud completion technique. In contrast to existing approaches, our method operates on 2D images formed by projecting the point cloud from several virtual camera positions around the object of interest. Both color and geometrical information is considered during the process, generating dense textured point clouds, displaying realistic patterns in the missing regions from the partial inputs. We present both quantitative and qualitative tests on various synthetic and real laser scanned vehicle point clouds, which demonstrate that our method surpasses existing state-of-the-art approaches. By applying it to vehicles from the Shapenet dataset, our approach outperforms recent techniques in terms of Earth Mover's Distance (EMD) and Chamfer Distance (CD) by 43.8% and 12.17%, respectively.

关键词： Point cloud compression visualization Three-dimensional displays Shape Urban areas Lasers Sensors

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Closing the Domain Gap for Cross-modal Visible-Infrared Vehicle Re-identification 26

Closing the Domain Gap for Cross-modal Visible-Infrared Vehi...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Kamenou, Eleni del Rincon, Jesus Martinez Miller, Paul Devlin-Hill, Patricia Queens Univ Ctr Secure Informat Technol CSIT Belfast Antrim North Ireland Thales UK Reading Berks England

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Traditional vehicle re-identification (ReID) approaches, based on visible spectrum data achieve high performance, but have limited capability of real-life applications, as they perform poorly under occluded visibility conditions, such as night-time and bad weather. In such cases, the use of infrared spectrum thermal imagery offers complementary and persistent information when the visual data contribution is inadequate. It is therefore highly beneficial to create a vehicle ReID framework that can exploit both modalities, if available, and is able to apply cross-modality matching, when ReID is required across single modal sensors. This is an extremely challenging task because the nature of the two data modalities induces high discrepancy between the two domains. In this paper we propose a robust end-to-end 2-stream vehicle ReID system that aims to solve the multi-modal and cross-modal ReID problem together by minimising the domain shift between infrared and visible distributions. Our framework consists of a shared network part, following the 2 independent streams, to extract shareable features, along with a domain alignment technique to narrow the gap between the two domains and inter-modality learning to address the cross-domain matching problem. The proposed system achieves state-of-the-art results on RGBN300 dataset, when both modalities are available at inference time. Moreover, our work is the first to explore the cross-modal settings for vehicle ReID and attempts to reduce the performance drop of the cross-modal scenario, when the query and the gallery images come from different modalities. We first measure the baseline cross-modal performance, and then prove that the proposed method improves up to 11% in mAP and 16% in Rank-1 score against the baseline.

关键词： Measurement visualization Data visualization Benchmark testing Feature extraction Sensors Pattern recognition

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A Novel Image Descriptor with Aggregated Semantic Skeleton Representation for Long-term Visual Place Recognition 26

A Novel Image Descriptor with Aggregated Semantic Skeleton R...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Nie, Jiwei Feng, Joe-Mei Xue, Dingyu Pan, Feng Liu, Wei Hu, Jun Cheng, Shuai Northeastern Univ Sch Informat Sci & Engn Shenyang Peoples R China Neusoft Reach Automot Technol Co Shenyang Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

In a Simultaneous Localization and Mapping (SLAM) system, loop-closure can eliminate accumulated errors, which is accomplished by Visual Place Recognition (VPR), a task that retrieves current scene from a set of pre-stored sequential images through matching specific scene-descriptors. In urban scenes, the appearance variation caused by seasons and illumination have brought great challenges to the robustness of scene descriptors. Semantic segmentation images can not only deliver the shape information of objects, but also their categories and spatial relations that will not be affected by the appearance-variation of the scene. Innovated by the Vector of Locally Aggregated Descriptor (VLAD), in this paper, we propose a novel image descriptor with aggregated semantic skeleton representation (SSR), dubbed SSR-VLAD, for the VPR under drastic appearance-variation of environments. The SSR-VLAD of one image aggregates the semantic skeleton features of each category, and encodes the spatial-temporal distribution information of the image semantic information. We conduct a series of experiments on three public datasets of challenging urban scenes. Compared with three state-of-the-art VPR methods- CoHog, NetVLAD, and Region-VLAD, VPR by matching SSR-VLAD outperforms those methods and maintains competitive real-time performance at the same time.

关键词： visualization Simultaneous localization and mapping Image recognition Shape Semantic segmentation Semantics Lighting

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Introduction to Special Issue on visualization Applied to Software Engineering

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information AND SOFTWARE TECHNOLOGY 2023年 155卷

作者： Leger, Paul Bergel, Alexandre Alcocer, Juan Pablo Sandoval Merino, Leonel Univ Catolica Norte Escuela Ingn Coquimbo Chile RelationalAI Zug Switzerland Pontificia Univ Catolica Chile Sch Engn DCC Santiago Chile Pontificia Univ Catolica Chile Sch Design DILAB Santiago Chile Pontificia Univ Catolica Chile Sch Engn Santiago Chile

Software visualization is a broad research area whose general goal is to enhance and promote the theory, realization, and evaluation of approaches to visually encode and analyze software systems, including software development practices, evolution, structure, and software runtime behavior. Software visualization is inherently interdisciplinary, drawing on theories and techniques from information visualization and computer graphics and applying these in the software engineering domain. This special issue on software visualization aims to bring together a community of researchers from software engineering, information visualization, computer graphics, human-computer interaction, and data science to discuss theoretical foundations, algorithms, techniques, tools, and applications related to software visualization. The special issue received 17 submissions of which 6 were accepted for publication (i.e., acceptance rate of 35.3%). Amongst the accepted papers, three correspond to extended versions of papers published in the IEEE Working conference on Software visualization (VISSOFT) 2021.

关键词： Software visualization Software evolution Software comprehension User studies

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Online Deep Clustering with Video Track Consistency 26

Online Deep Clustering with Video Track Consistency

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Alfani, Alessandra Becattini, Federico Seidenari, Lorenzo Del Bimbo, Alberto Univ Florence Florence FI Italy

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Several unsupervised and self-supervised approaches have been developed in recent years to learn visual features from large-scale unlabeled datasets. Their main drawback however is that these methods are hardly able to recognize visual features of the same object if it is simply rotated or the perspective of the camera changes. To overcome this limitation and at the same time exploit a useful source of supervision, we take into account video object tracks. Following the intuition that two patches in a track should have similar visual representations in a learned feature space, we adopt an unsupervised clustering based approach and constrain such representations to be labeled as the same category since they likely belong to the same object or object part. Experimental results on two downstream tasks on different datasets demonstrate the effectiveness of our Online Deep Clustering with Video Track Consistency (ODCT) approach compared to prior work, which did not leverage temporal information. In addition we show that exploiting an unsupervised class-agnostic, yet noisy, track generator yields to better accuracy compared to relying on costly and precise track annotations.

关键词： visualization Annotations Cameras Generators Pattern recognition Noise measurement Task analysis

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Efficient Fall Detection for a Healthcare Robot System Based on 3-Axis Accelerometer and Depth Sensor Fusion with LSTM Networks 26

Efficient Fall Detection for a Healthcare Robot System Based...

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26th International conference on Pattern Recognition / 8th International Workshop on Image Mining - theory and applications (IMTA)

作者： Kim, Kijung Yun, Guhnoo Park, Sung-Kee Kim, Dong Hwan Korea Inst Sci & Technol Ctr Intelligent & Interact Robot Seoul South Korea Korea Univ Dept Comp Sci & Engn Seoul South Korea

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Fall detection is one of the most important functions for a healthcare robot system because falls are very dangerous for older people and might lead to death if failed to provide prompt and adequate treatment. In this paper, we propose an efficient fall detection method based on 3-axis accelerometer and depth sensor fusion. LSTM networks are applied to handle temporal information. Simple low-level motion and pose features are obtained from each sensor data, and then fed into the LSTM networks that can learn high-level feature representations to classify falls from other daily life activities. Also, various learning tricks are combined to improve the performance. Experimental results show that the proposed fall detection method outperforms existing methods.

关键词： Accelerometers visualization Medical services Sensor fusion Vision sensors Robot sensing systems Feature extraction

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