• 제목/요약/키워드: object person

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카메라-레이저스캐너 상호보완 추적기를 이용한 이동 로봇의 사람 추종 (Person-following of a Mobile Robot using a Complementary Tracker with a Camera-laser Scanner)

  • 김형래;최학남;이재홍;이승준;김학일
    • 제어로봇시스템학회논문지
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    • 제20권1호
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    • pp.78-86
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    • 2014
  • This paper proposes a method of tracking an object for a person-following mobile robot by combining a monocular camera and a laser scanner, where each sensor can supplement the weaknesses of the other sensor. For human-robot interaction, a mobile robot needs to maintain a distance between a moving person and itself. Maintaining distance consists of two parts: object tracking and person-following. Object tracking consists of particle filtering and online learning using shape features which are extracted from an image. A monocular camera easily fails to track a person due to a narrow field-of-view and influence of illumination changes, and has therefore been used together with a laser scanner. After constructing the geometric relation between the differently oriented sensors, the proposed method demonstrates its robustness in tracking and following a person with a success rate of 94.7% in indoor environments with varying lighting conditions and even when a moving object is located between the robot and the person.

Viewpoint Invariant Person Re-Identification for Global Multi-Object Tracking with Non-Overlapping Cameras

  • Gwak, Jeonghwan;Park, Geunpyo;Jeon, Moongu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권4호
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    • pp.2075-2092
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    • 2017
  • Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

딥러닝 기반의 무기 소지자 탐지 (Armed person detection using Deep Learning)

  • 김건욱;이민훈;허유진;황기수;오승준
    • 방송공학회논문지
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    • 제23권6호
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    • pp.780-789
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    • 2018
  • 전 세계적으로 총기 사고는 인적이 드문 장소뿐만 아니라 사람들이 많이 모여 있는 공공장소에서도 빈번하게 일어난다. 특히, 권총과 같은 소형 총기 사고의 빈도수가 매우 높다. 그러므로 사람에 비해 상대적으로 매우 작은 크기의 객체인 권총을 가진 사람을 탐지하는 것은 사고의 피해를 최소화하는데 핵심적이다. '권총 든 사람'을 탐지하는 연구가 수행되고 있지만, 사람보다 권총은 상대적으로 크기가 작기 때문에 단일 객체만을 탐지하는 기존 객체 탐지 방법으로 '권총 든 사람'을 탐지하면 오류 발생 빈도수가 매우 높다. 이러한 문제점을 해결하기 위하여 권총으로 무장한 사람을 탐지하는 방법으로 APDA(Armed Person Detection Algorithm)를 제안한다. APDA는 입력 영상에서 합성곱신경망(Convolutional Neural Network, CNN) 기반의 인체 특징점 탐지 모델과 객체 탐지 모델을 병행하여 획득한 양 손목과 권총의 위치를 후처리 작업에서 이용하여 '권총 든 사람'을 탐지한다. APDA는 기존 방식보다 객관적 평가에서 재현율이 46.3% 향상되었고, 정밀도는 14.04% 향상되었다.

시선위치 추적기법 및 3차원 위치정보 획득이 가능한 사지장애인 보조용 웨어러블 로봇 시스템 (Wearable Robot System Enabling Gaze Tracking and 3D Position Acquisition for Assisting a Disabled Person with Disabled Limbs)

  • 서형규;김준철;정진형;김동환
    • 대한기계학회논문집A
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    • 제37권10호
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    • pp.1219-1227
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    • 2013
  • 눈 움직임만으로 물건을 집고자 하는 사지장애자를 위한 웨어러블 로봇을 소개한다. 이 로봇에서는 시선위치추적 알고리즘을 적용하여 파지하고자 하는 물체를 보는 동공의 움직임을 확인하여 물체의 2차원 정보를 구하고 물체까지의 깊이는 로봇 어깨위에 올려져 있는 Kinect라는 장치를 사용하여 구한다. 물체와 로봇, 그리고 카메라간의 좌표변환과 매칭을 통하여 최종 물체의 3차원 정보를 추출하고 이 정보는 로봇제어기인 DSP로 전송되어 물체를 잡을 수 있도록 제어하게 되어 궁극적으로 사용자가 물체를 정확히 잡을 수 있도록 한다.

액세서리 착용이 여성의 전문성 및 매력성 평가에 미치는 영향 (The Effect of Accessory Wearing on Professionalism and Attractiveness of Women)

  • 이명희
    • 한국의상디자인학회지
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    • 제8권1호
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    • pp.1-12
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    • 2006
  • The purpose of this study was to find out differences of women's professionalism and attractiveness according to the perceiver's level of interest on accessory, the object person's age, and accessory wearing. Subjects were 178 college women in Seoul. The evaluation of the accessory wearing was divided into five dimensions: professionalism, attractiveness, loveliness, femininity, and individuality. The look of accessory wearing had significant influences on the evaluation of professionalism and attractiveness. The women in their 40's wearing the scarf on a jacket were evaluatedhigh in professionalism, attractiveness, and femininity. The 40's wearing the cap with a T-shirt were evaluatedlow in professionalism and attractiveness. The women in their 20's wearing the cap with a T-shirt were evaluatedhigh in attractiveness and loveliness. Wearing of scarf enhanced professionalism, femininity, and individuality, wearing necklace enhanced femininity, and wearing cap enhanced loveliness of women. Perceiver's level of interest on accessory gave significant influences on perception of professionalism and attractiveness. The object person's age gave significant influences on loveliness, femininity, and individuality. Professionalism, attractiveness, loveliness, and femininity had interaction effects according to object person's age and accessories. When women in their 40's wore scarf or necklace, their professionalism was raised more than those in their 20's. Therefore accessory wearing was more effective to the women in their 40's than the 20's.

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Sparse M2M 환경을 위한 DTMNs 라우팅 프로토콜 (Sparse DTMNs routihg protocol for the M2M environment)

  • 왕종수;서두옥
    • 디지털산업정보학회논문지
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    • 제10권4호
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    • pp.11-18
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    • 2014
  • Recently, ICT technology has been evolving towards an M2M (Machine to Machine) environment that allows communication between machine and machine from the communication between person and person, and now the IoT (Internet of Things) technology that connects all things without human intervention is receiving great attention. In such a network environment, the communication network between object and object as well as between person and person, and person and object is available which leads to the sharing of information between all objects, which is the essential technical element for us to move forward to the information service society of the era of future ubiquitous computing. On this paper, the protocol related to DTMNs in a Sparse M2M environment was applied and the improved routing protocol was applied by using the azimuth and density of the moving node in order to support a more efficient network environment to deliver the message between nodes in an M2M environment. This paper intends to verify the continuity of the study related to efficient routing protocols to provide an efficient network environment in the IoT and IoE (Internet of Everything) environment which is as of recently in the spotlight.

시공간적으로 확장된 토폴로지를 이용한 개인 환경간 상호작용 파악 공간 분석 (Spatial Analysis to Capture Person Environment Interactions through Spatio-Temporally Extended Topology)

  • 이병재
    • 대한지리학회지
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    • 제47권3호
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    • pp.426-439
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    • 2012
  • 본 연구의 목적은 정성적인 개인의 공간 행동을 파악하고 행동 원인을 유추해 볼 수 있는 새로운 방법을 제안하는 것이다. 이동 객체의 단순한 기하학적인 움직임에 초점을 맞추는 것을 넘어서서, 사람과 환경 사이의 관계 변화 내지는 상호작용을 파악하여 이동 객체의 행동 특성을 분석할 수 있는 모델을 제시하고자 한다. 특히, 본 연구에서는 특정 지역의 경계 근처에서의 이동 객체의 움직임에 중점을 두고 분석하였다. 이동 객체의 영향력 범위를 적용하는 새로운 접근 방법을 이용하여 정성적인 개인 공간행위 특성을 파악하였다. 본 연구에서는, 이러한 객체를 시공간적으로 확장된 점(STEP)이라 명명하였으며, 그 영향력 범위를 그 객체의 위치와 함께 잠재적 사건이나 주변과의 상호작용이 가능한 구역으로 정의한다. STEP과 특정공간간의 관계 정량화를 위해, 위상 데이터 모델을 기반으로 2차원 공간에서의 특정 영역과 STEP 사이의 위상 관계를 나타내는 12 교차점 모델이 이용되었다. 이 연구에서는 이러한 STEP 개념의 관점에서, GPS추적 데이터를 이용한 프로토타입 응용 분석결과가 제공되었다.

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Multiple Person Tracking based on Spatial-temporal Information by Global Graph Clustering

  • Su, Yu-ting;Zhu, Xiao-rong;Nie, Wei-Zhi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권6호
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    • pp.2217-2229
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    • 2015
  • Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

Vision-based garbage dumping action detection for real-world surveillance platform

  • Yun, Kimin;Kwon, Yongjin;Oh, Sungchan;Moon, Jinyoung;Park, Jongyoul
    • ETRI Journal
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    • 제41권4호
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    • pp.494-505
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    • 2019
  • In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

다중 객체가 존재하는 ERP 영상에서 행동 인식 모델 성능 향상을 위한 전처리 기법 (Preprocessing Technique for Improving Action Recognition Performance in ERP Video with Multiple Objects)

  • 박은수;김승환;류은석
    • 방송공학회논문지
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    • 제25권3호
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    • pp.374-385
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    • 2020
  • 본 논문에서 Equirectangular Projection(ERP) 영상으로 행동 인식을 할 때의 문제점들을 해결할 수 있는 전처리 기법을 제안한다. 본 논문에서 제안하는 전처리 기법은 사람 객체를 행동의 주체 즉, Object of Interest(OOI)로 가정하고, OOI의 주변 영역을 ROI로 가정한다. 전처리 기법은 3개의 모듈로 이루어져 있다. I) 객체 인식 모델로 영상 내 사람 객체를 인식한다. II) 입력 영상에서 saliency map을 생성한다. III) 인식된 사람 객체와 saliency map을 이용하여 행동의 주체를 선정한다. 이후 행동 인식 모델에 선정된 행동의 주체 boundary box를 입력하여 행동 인식 성능을 높인다. 제안하는 전처리기법을 사용한 데이터를 행동 인식 모델에 입력한 방법의 성능과 원본 ERP 영상을 입력한 방법의 성능을 비교하였을 때 최대 99.6%의 성능 향상을 보이며, OOI가 감지되는 프레임만을 추출하였을 때 행동 관련 영상 요약의 효과도 볼 수 있다.