• Title/Summary/Keyword: Visual Object

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카메라 디포커싱을 이용한 로보트의 시각 서보

  • 신진우;고국현;조형석
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.559-564
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    • 1994
  • Recently, a visual servoing for an eye-in-hand robot has become an interesting problem. A distance between a camera and a task object is very useful information for visual servoing. In the previous works for visual servoing, the distance can be obtained from the difference between a reference and a measured feature value of the object such as area on image plane. However, since this feature depends on the object, the reference feature value must be changed when other task object is taken. To overcome this difficulty, this paper presents a novel method for visual servoing. In the proposed method, a blur is used to obtain the distance. The blur, one of the most important features, depends on the focal length of camera. Since it is not affected by the change of object, the reference feature value is not changed although other task object is taken. In this paper, we show a relationship between the distance and the blur, and define the feature jacobian matrix based on camera defocusing to operate the robot. A series of experiments is performed to verify the proposed method.

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Trends on Visual Object Tracking Using Siamese Network (Siamese 네트워크 기반 영상 객체 추적 기술 동향)

  • Oh, J.;Lee, J.
    • Electronics and Telecommunications Trends
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    • v.37 no.1
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    • pp.73-83
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    • 2022
  • Visual object tracking can be utilized in various applications and has attracted considerable attention in the field of computer vision. Visual object tracking technology is classified in various ways based on the number of tracking objects and the methodologies employed for tracking algorithms. This report briefly introduces the visual object tracking challenge that contributes to the development of single object tracking technology. Furthermore, we review ten Siamese network-based algorithms that have attracted attention, owing to their high tracking speed (despite the use of neural networks). In addition, we discuss the prospects of the Siamese network-based object tracking algorithms.

Visual Positioning System based on Voxel Labeling using Object Simultaneous Localization And Mapping

  • Jung, Tae-Won;Kim, In-Seon;Jung, Kye-Dong
    • International Journal of Advanced Culture Technology
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    • v.9 no.4
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    • pp.302-306
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    • 2021
  • Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

Visual Attention Algorithm for Object Recognition (물체 인식을 위한 시각 주목 알고리즘)

  • Ryu, Gwang-Geun;Lee, Sang-Hoon;Suh, Il-Hong
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.306-308
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    • 2006
  • We propose an attention based object recognition system, to recognize object fast and robustly. For this we calculate visual stimulus degrees and make saliency maps. Through this map we find a strongly attentive part of image by stimulus degrees, where local features are extracted to recognize objects.

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Improving visual relationship detection using linguistic and spatial cues

  • Jung, Jaewon;Park, Jongyoul
    • ETRI Journal
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    • v.42 no.3
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    • pp.399-410
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    • 2020
  • Detecting visual relationships in an image is important in an image understanding task. It enables higher image understanding tasks, that is, predicting the next scene and understanding what occurs in an image. A visual relationship comprises of a subject, a predicate, and an object, and is related to visual, language, and spatial cues. The predicate explains the relationship between the subject and object and can be categorized into different categories such as prepositions and verbs. A large visual gap exists although the visual relationship is included in the same predicate. This study improves upon a previous study (that uses language cues using two losses) and a spatial cue (that only includes individual information) by adding relative information on the subject and object of the extant study. The architectural limitation is demonstrated and is overcome to detect all zero-shot visual relationships. A new problem is discovered, and an explanation of how it decreases performance is provided. The experiment is conducted on the VRD and VG datasets and a significant improvement over previous results is obtained.

Visual servoing based on neuro-fuzzy model

  • Jun, Hyo-Byung;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.712-715
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    • 1997
  • In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

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Multiple Object-Based Design Model for Quality Improvement of User Interface (사용자 인터페이스 품질 향상을 위한 다중 객체 기반 설계 모델)

  • Kim Jeong-Ok;Lee Sang-Young
    • The KIPS Transactions:PartD
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    • v.12D no.7 s.103
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    • pp.957-964
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    • 2005
  • According to rapid growth of web environment, user interface design needs to support the complex interactions between human and computer. In the paper we suggest the object modeling method for Qualify Improvement of User Interface. We propose the 4 business event's object modeling phases such as business event object modeling, task object modeling, transaction object modeling, and form object modeling to enhance visual cohesion of UI. As a result, this 4 phases in this paper allows us to enhance visual cohesion of User Interface prototype. We have found that the visual cohesion of business events become strong and unskilled designer can develope the qualified user interface prototype. And it also improves understanding of business task and reduces prototype system development iteration.

Implementation and Experimentation of Tracking Control of a Moving Object for Humanoid Robot Arms ROBOKER by Stereo Vision (스테레오 비전정보를 사용한 휴머노이드 로봇 팔 ROBOKER의 동적 물체 추종제어 구현 및 실험)

  • Lee, Woon-Kyu;Kim, Dong-Min;Choi, Ho-Jin;Kim, Jeong-Seob;Jung, Seul
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.10
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    • pp.998-1004
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    • 2008
  • In this paper, a visual servoing control technique of humanoid robot arms is implemented for tracking a moving object. An embedded time-delayed controller is designed on an FPGA(Programmable field gate array) chip and implemented to control humanoid robot arms. The position of the moving object is detected by a stereo vision camera and converted to joint commands through the inverse kinematics. Then the robot arm performs visual servoing control to track a moving object in real time fashion. Experimental studies are conducted and results demonstrate the feasibility of the visual feedback control method for a moving object tracking task by the humanoid robot arms called the ROBOKER.

Effects of Sensory Integration Therapy and Home-Based Sensory Integration on Visual Attention in Children with Down Syndrome (감각통합치료와 가정프로그램 중재병행이 다운증후군 아동의 시각적 주의력에 미치는 효과: 단일사례연구)

  • Son, Ji-Won;Lee, Hye-Rim
    • The Journal of Korean Academy of Sensory Integration
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    • v.21 no.2
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    • pp.12-23
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    • 2023
  • Objective : The purpose of this study was to investigate the effect of sensory integration therapy and home program intervention on the visual attention of children with Down syndrome. Methods : This study used a single subject design for one child with Down syndrome, Sensory integrated treatment intervention was conducted once a week for 16 weeks, and home programs were conducted four times a week for 16 weeks. Changes in visual attention were measured after intervention in the target child. Results : After the intervention, the average values of object gaze, object horizontal pursuit, and object vertical pursuit time increased compared with the baseline period. In object gaze, object horizontal pursuit, and object vertical pursuit, a section higher than the ±2 standard deviation of the baseline period was observed during the intervention period. Conclusion : This study confirmed that the combination of sensory integrated therapy and home program intervention improved visual attention and visual perception in children with Down syndrome, and it is meaningful that it presented an effective intervention method.