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2023 IEEE International Conference on Image Processing Challenges and Workshops, ICIPCW 2023

作者： Seibt, Simon Von Rymon Lipinski, Bartosz Chang, Thomas Latoschik, Marc Erich Nuremberg Institute of Technology Game Tech Lab Faculty of Computer Science Nuremberg Germany Institute of Computer Science University of Wuerzburg Human-Computer Interaction Group Wuerzburg Germany

ISBN: (纸本)9798350302585

Structure from motion (SfM) is a fundamental task in computer vision and allows recovering the 3D structure of a stationary scene from an image set. Finding robust and accurate feature matches plays a crucial role in the early stages of SfM. So in this work, we propose a novel method for computing image correspondences based on dense feature matching (DFM) using homographic decomposition: The underlying pipeline provides refinement of existing matches through iterative rematching, detection of occlusions and extrapolation of additional matches in critical image areas between image pairs. Our main contributions are improvements of DFM specifically for SfM, resulting in global refinement and global extrapolation of image correspondences between related views. Furthermore, we propose an iterative version of the Delaunay-triangulation-based outlier detection algorithm for robust processing of repeated image patterns. Through experiments, we demonstrate that the proposed method significantlv improves the reconstruction accuracy. © 2023 IEEE.

关键词： computer vision

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SOS: Segment Object System for Open-World Instance Segmentation With Object Priors

arXiv

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arXiv 2024年

作者： Wilms, Christian Rolff, Tim Hillemann, Maris Johanson, Robert Frintrop, Simone Computer Vision Group University of Hamburg Germany Human-Computer Interaction Group University of Hamburg Germany

We propose an approach for Open-World Instance Segmentation (OWIS), a task that aims to segment arbitrary unknown objects in images by generalizing from a limited set of annotated object classes during training. Our Segment Object System (SOS) explicitly addresses the generalization ability and the low precision of state-of-the-art systems, which often generate background detections. To this end, we generate high-quality pseudo annotations based on the foundation model SAM [27]. We thoroughly study various object priors to generate prompts for SAM, explicitly focusing the foundation model on objects. The strongest object priors were obtained by self-attention maps from self-supervised vision Transformers, which we utilize for prompting SAM. Finally, the post-processed segments from SAM are used as pseudo annotations to train a standard instance segmentation system. Our approach shows strong generalization capabilities on COCO, LVIS, and ADE20k datasets and improves on the precision by up to 81.6% compared to the state-of-the-art. Source code is available at: https: //***/chwilms/SOS Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Robotic Sorting of Mechanical and Electrical Parts: An Autonomous vision-Based Approach in a Practical Case Study 10

Robotic Sorting of Mechanical and Electrical Parts: An Auton...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Yousefi, Mohammad Dalvand, Mahdi Khomami, Navid Asadi Masouleh, Mehdi Tale Yazdi, Mohammad Reza Haeri University of Tehran Human and Robot Interaction Lab. School of Mechanical Engineering Tehran Iran University of Tehran Human and Robot Interaction Lab. School of Electrical and Computer Engineering Tehran Iran University of Tehran School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798331509972

In today's industrial landscape, automation has become increasingly vital, particularly in the deployment of robots for tasks such as sorting machine components. The use of robotic systems enhances process accuracy and speed, resulting in significant cost reductions and improved productivity compared to manual labor. This paper aims to design and develop an automated sorting system for various types of mechanical and electrical parts, utilizing image processing and machine vision algorithms with a Delta parallel robot equipped with a two-finger gripper. The target mechanical and electrical parts in this study are screws, nuts, metal washers, rubber washers, retaining rings, rectangular keys, wall plugs, resistors, potentiometers, capacitors, batteries, ICs, and LEDs. The YOLOv3 algorithm and Adaptive Thresholding method are employed to detect and distinguish objects from the background, and size measurement is achieved with the help of a custom marker with known dimensions. In this study, transfer learning based on pre-Trained weights of YOLOv3 for the COCO dataset is applied. The proposed system attains a final mean Average Precision (mAP@0.5) value exceeding 0.95 for part detection using YOLOv3. Additionally, it demonstrates an overall pick-And-place success rate exceeding 90%. © 2024 IEEE.

关键词： Grippers

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Handwritten Character String Recognition Using Transformer and CNN Features

Handwritten Character String Recognition Using Transformer a...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Shunya Rakuka Kento Morita Tetsushi Wakabayashi Human Computer Interaction Lab Mie University

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

While character recognition systems applications with restrictions on writing conditions, such as zip code recognition and ledger sheet recognition, are in practical use, the accuracy of free handwritten character string recognition is still low and there are many challenges. Japanese free handwritten character strings are difficult to segment because some Japanese characters consist of multiple connected components and there are no spaces between words. Therefore, in this study, we propose a method for handwritten character string recognition method that does not require character segmentation using Transformer and CNN features. Transformer-based models usually require a large amount of annotated training data. However, our method can be trained with a small amount of annotated training data. Comparative experiments confirm the effectiveness of the proposed method by achieving CER=O.127 while CRNN [1] and TrOCR [2] achieve CER=O.562 and CER=O.174, respectively. The results show that the proposed method is effective for Japanese character string recognition, where the variety of character strings is large and it is difficult to secure a sufficient number of training samples for each character string.

关键词： Training Handwriting recognition Image recognition Accuracy Training data Writing Transformers Data models Decoding Character recognition

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Generating a General Culturing Microorganism Pattern Using a Delta Parallel Robot and Cam-in-Hand Calibration Method 11

Generating a General Culturing Microorganism Pattern Using a...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Pasiar, Navid Mohammadi, Arvin Ahangar, Sajjad Khomami, Navid Asadi Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Lab. Department of Mechanical Eng. Tehran Iran University of Tehran Human and Robot Interaction Lab. Tehran Iran University of Tehran Human and Robot Interaction Lab. School of Electrical and Computer Eng. Tehran Iran

ISBN: (纸本)9798350308105

Robots can play a vital role in laboratory tasks, especially in culturing microorganisms. Currently, many of these operations are performed manually, which leads to biased and irreproducible results. This paper explores a calibration method for minimizing errors of a performing two certain laboratory tasks of swabbing and pipetting. This leads to enhanced accuracy and productivity. This research intends to culture microorganisms in a petri-dish in a specific pattern, measuring the coordinates of each object in the output image so the object location in the real world can be calculated. This research investigates the Cam-in-Hand method for a Delta Parallel Robot, meaning that the camera is mounted on the End-Effector. In this approach, a method of translating image coordinates into real-world coordinates is introduced. It is essential to provide an additional coordinate (in this case $z -$value) before the conversion, given that the camera outputs a 2D image. A vector-based image, in SVG format, as input to the algorithm generates a set of coordinates which determines the main points for swabbing or pipetting operation. Using this data, an array of coordinates is linearly interpolated in 3D space for the swabbing operation. Conversely, the trajectory generated for pipetting uses the 4-5-6-7 interpolating polynomial. The robot then adheres to following the interpolated array of coordinates as a function of time, using a PID controller. The pipetting device is built with a 3D printer using PLA materials. The calibration is done in different heights. The Camin-Hand method leads to ±1 cm precision as a result. Minimum, maximum, and mean errors are 0.092,1.61 and 0.76 respectively for the central point. © 2023 IEEE.

关键词： Calibration

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Autonomous vision-based Robotic Grasping of Household Objects: A Practical Case Study 11

Autonomous Vision-based Robotic Grasping of Household Object...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Roudbari, Asal Dalvand, Mahdi Pasiar, Navid Asadi, Navid Yousefi, Mohammad Masouleh, Mehdi Tale Sharif University of Technology Electrical Engineering Department Tehran Iran University of Tehran Human Robot Interaction Lab Tehran Iran University of Tehran Human Robot Interaction Lab School of Electrical Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

Autonomous robotic grasping has emerged as a valuable capability for automating everyday household tasks like table setting (bossing), cleaning, and meal preparation. Still, accurately detecting and manipulating diverse everyday objects in unstructured home environments remains a significant challenge. In this study, an integrated robotic system combining YOLOv8s-seg deep learning for object detection and segmentation with computer vision techniques to determine optimal grasping points is proposed. The accuracy of this model has also been compared with other models through their mAP0.5, mAP.05-.95, precision and recall. A custom dataset of over 1000 images containing common household objects was created, with manual annotation and augmentation to train the YOLOv8s-seg segmentation model. The approach processes input images to understand desired arrangements and identify target objects and their locations for grasping. The detected objects are localized using camera-to-robot calibration and aligned with estimated orientations from computer vision techniques. Extensive tests have proven that representative household objects in cluttered arrangements have a grasping success rate of over 90% using a 3DOF Delta Parallel robot with a 2-finger gripper guided entirely by visual perception. By overcoming real-world challenges like transparent and reflective materials, the perception-guided robots provide precise and efficient robotic grasping in unstructured home environments. This integrated approach combines robust perception and localization, providing promising evidence for reliable automation of repetitive household organization tasks1.1A video of real-time grasp performance is uploaded as supplementary material. © 2023 IEEE.

关键词： Object detection

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Robust PID Control of Robot Manipulator Using Time Delay Control Design Approach 11

Robust PID Control of Robot Manipulator Using Time Delay Con...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Fateh, Alireza Momeni, Hamidreza Masouleh, Mehdi Tale Tarbiat Modares University Dept. of Electrical and Computer Eng Tehran Iran University of Tehran Human and Robot Interaction Lab School of Electrical and Computer Eng Tehran Iran

ISBN: (纸本)9798350308105

Time Delay Control (TDC) is recognized as a simple yet effective alternative to model-based or intelligent-based control due to its simplicity and robustness. Proportional-Integral-Derivative (PID) control is one of the industry's most used and straightforward control schemes. While this approach has proven to be effective, the tuning of its coefficients has remained a difficult task. Though showing similar performance, a definite connection between the two approaches has yet to be defined. In this paper, by taking advantage of padé approximation, a direct connection between the two control methods coefficients is obtained. As a result, a new approach for choosing the classical PID controller coefficients is introduced using TDC as the primary control scheme design framework, which has led to a decrease in the number of required control design coefficients of the PID control system. Further on, the uniformly ultimately bounded stability of the control system under bounded external disturbances is proven. Finally, via simulations on the SCARA robot, the obtained results and the validity of the proposed connection are explored. © 2023 IEEE.

关键词： Time delay

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Road Sign Classification Using Transfer Learning and Pre-trained CNN Models 1

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1st International Conference on Artificial Intelligence and Smart Vehicles, ICAISV 2023

作者： Hosseini, Seyed Hossein Ghaderi, Foad Moshiri, Behzad Norouzi, Mojtaba Human Computer Interaction Lab Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran School of ECE University of Science and Technology Tehran Iran

ISBN: (数字)9783031437632

ISBN: (纸本)9783031437625

In this paper, we propose a transfer learning-based approach for road sign classification using pre-trained CNN models. We evaluate the performance of our fine-tuned VGG-16, VGG-19, ResNet50 and EfficientNetB0 models on the German Traffic Sign Recognition Benchmark (GTSRB) test dataset. Our work makes several contributions, including the utilization of transfer learning with pre-trained CNN models, the integration of augmentation techniques, and a comprehensive evaluation of multiple state-of-the-art architectures on the road sign classification task. Our experimental results show that the proposed approach achieves an average accuracy of 99.2% on the GTSRB test dataset, outperforming existing state-of-the-art approaches. The results confirm that transfer learning and pre-trained models can significantly improve the accuracy of road sign classification, even with a relatively small dataset. Our study contributes to the field of intelligent transportation systems by providing an efficient and accurate method for road sign classification. We believe that our approach can be easily extended to other computer vision tasks and applied to real-world scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Autonomous vehicles

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Being Meaningful: Weaving Soma-Reflective Technological Mediations into the Fabric of Daily Life 23

Being Meaningful: Weaving Soma-Reflective Technological Medi...

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17th International Conference on Tangible, Embedded, and Embodied interaction, TEI 2023

作者： Haynes, Alice Reed, Courtney Nordmoen, Charlotte Skach, Sophie Human Computer Interaction Lab University of Saarland Germany Sensorimotor Interaction Max Planck Institute for Informatics Saarland Informatics Campus Germany Queen Mary University of London London United Kingdom

ISBN: (纸本)9781450399777

A one-size-fits-all design mentality, rooted in objective efficiency, is ubiquitous in our mass-production society. This can negate peoples' experiences, bodies, and narratives. Ongoing HCI research proposes design for meaningful relations;but for many researchers, the practical implementation of these philosophies remains somewhat intangible. In this Studio, we playfully tackle this space by engaging with the nuances of soft, flexible, and organic materials, collectively designing probes to embrace plurality, embody meaning, and encourage soma-reflection. Focusing on materiality and practices from e-textiles, soft robotics, and biomaterials research, we address technology's role as a mediator of our experiences and determiner of our realities. The processes and probes developed in this Studio will serve as an experiential manifesto, providing practitioners with tools to deepen their own practices for designing soma-reflective tangible and embodied interaction. The Studio will form the first steps for ongoing collaboration, focusing on bespoke design and curation of meaningful, personal relationships. © 2023 Owner/Author.

关键词： Weaving

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Evaluation Criteria and Assessments for Effective User Experiences, Web Accessibility, and interaction for Visually Impaired Users 8th

Evaluation Criteria and Assessments for Effective User Exper...

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8th International Conference on Computational Science and Technology, ICCST 2021

作者： Jantan, Azrul Hazri Yazid, Mariam Azwa Husain, Wan Nur Liyana Wan Human-Computer Interaction Research Lab Faculty of Computer Science and Information Technology Universiti Putra Malaysia Selangor43400 Malaysia

ISBN: (纸本)9789811685149

To date, the advancement in web and internet technologies have changed the way on how people interact with computer software/application. Information is much easier to accessed, processes can be performed faster, and interaction can be controlled fully by users. However, the complexity of the web accessibility, application interaction, and components of user experience were also increasing. Thus, to fulfil the web usability requirements and its comprehensiveness, web experts’ verification and validation are required to support the overall design modelling including its internal strength of the domain. This paper will elaborate and discuss the main criteria included in the verification and validation processes towards visually impaired users. We built our evaluation (usability) criteria based on previous research and represent them as questionnaire for qualitative assessment of a web application. The main objective is to propose the best evaluation criteria for a web evaluation and assessment usability to support the design modelling and interaction effectiveness among visually impaired users. It will include better technology understanding on both design and evaluation criteria of the whole domain structure including their interactivity that reflect the web accessibility, application interaction, and user experience components. The proposed evaluation criteria will be focusing on three section, called interaction characteristics, user experience components, and the outcome of the final judgement. We envisage effective and comprehensive evaluation criteria that could be integrated and provide positive feedback from the experts’ review and their findings. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Usability engineering

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