• 제목/요약/키워드: 3D Visual Object Recognition

검색결과 25건 처리시간 0.041초

인공지능 객체인식에 관한 파라미터 측정 연구 (A Study On Parameter Measurement for Artificial Intelligence Object Recognition)

  • 최병관
    • 디지털산업정보학회논문지
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    • 제15권3호
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    • pp.15-28
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    • 2019
  • Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

3차원 물체의 인식 성능 향상을 위한 감각 융합 시스템 (Sensor Fusion System for Improving the Recognition Performance of 3D Object)

  • Kim, Ji-Kyoung;Oh, Yeong-Jae;Chong, Kab-Sung;Wee, Jae-Woo;Lee, Chong-Ho
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.107-109
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    • 2004
  • In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile information. The proposed system focuses on improving recognition performance of 3D object. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse these informations. Tactual signals are obtained from the reaction force by the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of teaming iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though visual information has a defect. The experimental results show that the proposed system can improve recognition rate and reduce learning time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme of 3D object.

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다면기법 SPFACS 영상객체를 이용한 AAM 알고리즘 적용 미소검출 설계 분석 (Using a Multi-Faced Technique SPFACS Video Object Design Analysis of The AAM Algorithm Applies Smile Detection)

  • 최병관
    • 디지털산업정보학회논문지
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    • 제11권3호
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    • pp.99-112
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    • 2015
  • Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

3차원 물체의 인식 성능 향상을 위한 감각 융합 신경망 시스템 (Neural Network Approach to Sensor Fusion System for Improving the Recognition Performance of 3D Objects)

  • 동성수;이종호;김지경
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권3호
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    • pp.156-165
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    • 2005
  • Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

Resolution-enhanced Reconstruction of 3D Object Using Depth-reversed Elemental Images for Partially Occluded Object Recognitionz

  • Wei, Tan-Chun;Shin, Dong-Hak;Lee, Byung-Gook
    • Journal of the Optical Society of Korea
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    • 제13권1호
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    • pp.139-145
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    • 2009
  • Computational integral imaging (CII) is a new method for 3D imaging and visualization. However, it suffers from seriously poor image quality of the reconstructed image as the reconstructed image plane increases. In this paper, to overcome this problem, we propose a CII method based on a smart pixel mapping (SPM) technique for partially occluded 3D object recognition, in which the object to be recognized is located at far distance from the lenslet array. In the SPM-based CII, the use of SPM moves a far 3D object toward the near lenslet array and then improves the image quality of the reconstructed image. To show the usefulness of the proposed method, we carry out some experiments for occluded objects and present the experimental results.

이동로봇의 물체인식 기반 전역적 자기위치 추정 (Object Recognition-based Global Localization for Mobile Robots)

  • 박순용;박민용;박성기
    • 로봇학회논문지
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    • 제3권1호
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    • pp.33-41
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    • 2008
  • Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

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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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    • 제9권4호
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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 Servoing of a Mobile Manipulator Based on Stereo Vision

  • Lee, H.J.;Park, M.G.;Lee, M.C.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.767-771
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    • 2003
  • In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. However, color information is useful for simple recognition in real-time visual servoing. In this paper, we refer to about object recognition using colors, stereo matching method, recovery of 3D space and the visual servoing.

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스테레오 영상을 이용한 이동형 머니퓰레이터의 시각제어 (Visual Servoing of a Mobile Manipulator Based on Stereo Vision)

  • 이현정;박민규;이민철
    • 제어로봇시스템학회논문지
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    • 제11권5호
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    • pp.411-417
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    • 2005
  • In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the potion of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. Color information is useful for simple recognition in real-time visual servoing. This paper addresses object recognition using colors, stereo matching method to reduce its calculation time, recovery of 3D space and the visual servoing.

실내 환경에서 Chirp Emission과 Echo Signal을 이용한 심층신경망 기반 객체 감지 기법 (DECODE: A Novel Method of DEep CNN-based Object DEtection using Chirps Emission and Echo Signals in Indoor Environment)

  • 남현수;정종필
    • 한국인터넷방송통신학회논문지
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    • 제21권3호
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    • pp.59-66
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    • 2021
  • 인간은 오감 (시각, 청각, 후각, 촉각, 미각) 중 시각 및 청각 정보를 위주로 사용하여 주변 물체를 인식한다. 최신의 객체 인식과 관련한 주요 연구에서는 주로 이미지센서 정보를 이용한 분석에 초점이 맞추어져 있다. 본 논문에서는 다양한 chirp 오디오 신호를 관측공간에 방출하고 2채널 수신센서를 통해 echo를 수집하여 스펙트럼 이미지로 변화시킨 후 딥러닝을 기반으로 이미지 학습 알고리즘을 이용하여 3D 공간상의 객체 인식 실험을 진행하였다. 본 실험은 무향실의 이상적 조건이 아닌 일반적인 실내 환경에서 발생하는 잡음 및 echo가 있는 환경에서 실험을 진행하였고 echo를 통해 객체 인식률을 83% 정확도로 물체의 위치 추정할 수 있었다. 또 한 추론 결과를 관측공간과 3D Sound 공간 신호로 mapping 하여 소리로 출력하여 3D 사운드의 학습을 통해 소리를 통한 시각 정보를 얻을 수 있었다. 이는 객체 인식 연구를 위해서 이미지 정보와 함께 다양한 echo 정보의 활용이 요구된다는 의미이며 이런 기술을 3D 사운드를 통한 증강현실 등에 활용 가능할 것이다.