• Title/Summary/Keyword: object person

Search Result 368, Processing Time 0.025 seconds

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

  • Kim, Hyoung-Rae;Cui, Xue-Nan;Lee, Jae-Hong;Lee, Seung-Jun;Kim, Hakil
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.20 no.1
    • /
    • pp.78-86
    • /
    • 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)
    • /
    • v.11 no.4
    • /
    • pp.2075-2092
    • /
    • 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.

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

  • Kim, Geonuk;Lee, Minhun;Huh, Yoojin;Hwang, Gisu;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
    • /
    • v.23 no.6
    • /
    • pp.780-789
    • /
    • 2018
  • Nowadays, gun crimes occur very frequently not only in public places but in alleyways around the world. In particular, it is essential to detect a person armed by a pistol to prevent those crimes since small guns, such as pistols, are often used for those crimes. Because conventional works for armed person detection have treated an armed person as a single object in an input image, their accuracy is very low. The reason for the low accuracy comes from the fact that the gunman is treated as a single object although the pistol is a relatively much smaller object than the person. To solve this problem, we propose a novel algorithm called APDA(Armed Person Detection Algorithm). APDA detects the armed person using in a post-processing the positions of both wrists and the pistol achieved by the CNN-based human body feature detection model and the pistol detection model, respectively. We show that APDA can provide both 46.3% better recall and 14.04% better precision than SSD-MobileNet.

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

  • Seo, Hyoung Kyu;Kim, Jun Cheol;Jung, Jin Hyung;Kim, Dong Hwan
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.37 no.10
    • /
    • pp.1219-1227
    • /
    • 2013
  • A new type of wearable robot is developed for a disabled person with disabled limbs, that is, a person who cannot intentionally move his/her legs and arms. This robot can enable the disabled person to grip an object using eye movements. A gaze tracking algorithm is employed to detect pupil movements by which the person observes the object to be gripped. By using this gaze tracking 2D information, the object is identified and the distance to the object is measured using a Kinect device installed on the robot shoulder. By using several coordinate transformations and a matching scheme, the final 3D information about the object from the base frame can be clearly identified, and the final position data is transmitted to the DSP-controlled robot controller, which enables the target object to be gripped successfully.

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

  • Lee Myoung-Hee
    • Journal of the Korea Fashion and Costume Design Association
    • /
    • v.8 no.1
    • /
    • pp.1-12
    • /
    • 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.

  • PDF

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

  • Wang, Jong Soo;Seo, Doo Ok
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.10 no.4
    • /
    • pp.11-18
    • /
    • 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.

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

  • Lee, Byoung-Jae
    • Journal of the Korean Geographical Society
    • /
    • v.47 no.3
    • /
    • pp.426-439
    • /
    • 2012
  • The goal of this study is to propose a new method to capture the qualitative person spatial behavior. Beyond tracking or indexing the change of the location of a person, the changes in the relationships between a person and its environment are considered as the main source for the formal model of this study. Specifically, this paper focuses on the movement behavior of a person near the boundary of a region. To capture the behavior of person near the boundary of regions, a new formal approach for integrating an object's scope of influence is described. Such an object, a spatio-temporally extended point (STEP), is considered here by addressing its scope of influence as potential events or interactions area in conjunction with its location. The formalism presented is based on a topological data model and introduces a 12-intersection model to represent the topological relations between a region and the STEP in 2-dimensional space. From the perspective of STEP concept, a prototype analysis results are provided by using GPS tracking data in real world.

  • PDF

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)
    • /
    • v.9 no.6
    • /
    • pp.2217-2229
    • /
    • 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
    • /
    • v.41 no.4
    • /
    • pp.494-505
    • /
    • 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.

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

  • Park, Eun-Soo;Kim, Seunghwan;Ryu, Eun-Seok
    • Journal of Broadcast Engineering
    • /
    • v.25 no.3
    • /
    • pp.374-385
    • /
    • 2020
  • In this paper, we propose a preprocessing technique to solve the problems of action recognition with Equirectangular Projection (ERP) video. The preprocessing technique proposed in this paper assumes the person object as the subject of action, that is, the Object of Interest (OOI), and the surrounding area of the OOI as the ROI. The preprocessing technique consists of three modules. I) Recognize person object in the image with object recognition model. II) Create a saliency map from the input image. III) Select subject of action using recognized person object and saliency map. The subject boundary box of the selected action is input to the action recognition model in order to improve the action recognition performance. When comparing the performance of the proposed preprocessing method to the action recognition model and the performance of the original ERP image input method, the performance is improved up to 99.6%, and the action is obtained when only the OOI is detected. It can also see the effects of related video summaries.