• Title/Summary/Keyword: 스켈레톤 모델

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Using Skeleton Vector Information and RNN Learning Behavior Recognition Algorithm (스켈레톤 벡터 정보와 RNN 학습을 이용한 행동인식 알고리즘)

  • Kim, Mi-Kyung;Cha, Eui-Young
    • Journal of Broadcast Engineering
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    • v.23 no.5
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    • pp.598-605
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    • 2018
  • Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

Realistic 3D tree growth simulation from one image (한 장의 영상을 이용한 사실적 나무 생장표현)

  • Kim, Jae-Hwan;Jeong, Il-Kwon
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06c
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    • pp.362-363
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    • 2012
  • 본 논문에서는 한 장의 실제 나무 영상이 주어졌을 시, 사실적인 3차원 나무 모델링(modeling) 및 자가생장(self-growth) 표현을 위한 방법을 소개하도록 한다. 스켈레톤기반의 간략화(skeleton-based abstraction)를 이용하여 동일한 나무 몸통(trunk)을 갖는 다양한 나무 모델생성과 함께 나무의 다면체구조(manifold structure)를 고려한 지오데식 커널(geodesic kernel)을 이용하여 나무의 자가생장을 표현한다. 나무의 자가생장은 사전 정의된 나무 굵기, 전체 크기, 그리고 가지증식 순서정보와 같은 상대적 성장정보(allometric information)를 동시 이용하여 상대적인 나무 생장(allometric tree growth)을 표현하도록한다. 한편, 보여지지않는 나무 가지와 잎들에 대해선, 나무구조는 로컬하게 자기유사성(local self-similarity)을 갖는다라는 고전적인 절차적(conventional procedural) 가정을 이용하여 자동적으로 생성토록한다. 실제영상을 이용한 몇몇들의 실험을 통해 보다 효과적으로 나무 모델 및 생장 표현이 가능함을 보여주도록한다.

Fall Early Response System Using Pose Recognition Technology Based on Skeleton Model (스켈레톤 모델 기반의 포즈 인식 기술을 활용한 낙상 조기 대응 시스템)

  • Woo-hyuk Jung;Geun-jae Lee;Chan-seok Bae;Gyu-ryang Hong;Ji-hyun Kwon;Hongseok Yoo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.479-480
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    • 2023
  • 현대 사회는 출생아가 줄어들고 고령화 현상이 빠르게 진행 중이다. 20~30대의 사회 복지 종사자가 줄어들고 노인 인구는 늘어나는 반비례 현상이 나타나고 있다. 보호자가 없는 노인에게 낙상 사고와 같은 위급상황이 발생한다면 골든타임을 놓칠 수도 있을 것이다. 따라서, 본 논문에서는 낙상 사고 발생 시, 빠른 시간 내에 실시간 모니터링을 통해 노인 복지사가 상황을 인지할 수 있게 하는 시스템을 개발하였다. 미디어파이프 포즈 모델을 이용하여 관찰 대상의 움직임을 포착하도록 하였고 PTZ 카메라의 서보 모터 제어를 통해 포착한 관찰 대상을 추적하도록 하였다. 주요 장면은 사진으로 저장해 웹 서버로 전송하고, 심박수 측정 센서와 와이파이 통신 모듈이 장착된 아두이노 보드가 실시간으로 웹 서버로 전송하여, 전담 관리자는 사진을 통해 상황을 인식하고 심박수를 보고 얼마나 위급한지 알 수 있도록 하였다.

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Object surveillance and unusual-behavior judgment using Network Camera (네트워크 카메라를 이용한 물체 감시와 비정상행위 판단)

  • Kim, Jin-Gyu;Kim, Jong-Sun;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1910-1911
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    • 2011
  • 본 논문에서는 네트워크 카메라를 이용한 물체 감시 및 비정상 행위의 판단을 위한 실시간 시스템을 제안한다. 제안된 시스템은 먼저 물체의 감시를 위해 SIFT 알고리즘에 기반으로 감시 물체의 특징 정보를 DB화 하고, 히스토그램(Histogram)기법을 활용하여 감시지역을 설정한다. 또한 인간의 행동 및 비정상 행위를 판단하기 위하여, 가상 인간 스켈레톤 모델을 이용하여 입력된 영상에서의 인간의 특징점을 추출한다. 추출된 특징점을 바탕으로 PCA(Principal Component Analysis)를 이용하여 인간의 움직임을 보다 정확하게 표현할 수 있는 특징벡터를 생성하였다. 생성된 특징벡터를 기반으로 퍼지분류기를 이용하여 인간의 행동을 분류하고, 생성된 특징벡터와 특정물체의 거리를 기반으로 인간의 비정상행위를 판단한다. 제안된 방법은 실험을 통해 시스템의 응용 가능성을 증명한다.

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The Study of Skeleton System for Facial Expression Animation (Skeleton System으로 운용되는 얼굴표정 애니메이션에 관한 연구)

  • Oh, Seong-Suk
    • Journal of Korea Game Society
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    • v.8 no.2
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    • pp.47-55
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    • 2008
  • This paper introduces that SSFE(Skeleton System for Facial Expression) to deform facial expressions by rigging of skeletons does same functions with 14 facial muscles based on anatomy. A three dimensional animation tool (MAYA 8.5) is utilized for making the SSFE that presents deformation of mesh models implementing facial expressions around eyes, nose and mouse. The SSFE has a good reusability within diverse human mesh models. The reusability of SSFE can be understood as OSMU(One Source Multi Use) of three dimensional animation production method. It can be a good alternative technique for reducing production budget of animations. It can also be used for three dimensional animation industries such as virtual reality and game.

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Realtime Human Object Segmentation Using Image and Skeleton Characteristics (영상 특성과 스켈레톤 분석을 이용한 실시간 인간 객체 추출)

  • Kim, Minjoon;Lee, Zucheul;Kim, Wonha
    • Journal of Broadcast Engineering
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    • v.21 no.5
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    • pp.782-791
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    • 2016
  • The object segmentation algorithm from the background could be used for object recognition and tracking, and many applications. To segment objects, this paper proposes a method that refer to several initial frames with real-time processing at fixed camera. First we suggest the probability model to segment object and background and we enhance the performance of algorithm analyzing the color consistency and focus characteristic of camera for several initial frames. We compensate the segmentation result by using human skeleton characteristic among extracted objects. Last the proposed method has the applicability for various mobile application as we minimize computing complexity for real-time video processing.

STAGCN-based Human Action Recognition System for Immersive Large-Scale Signage Content (몰입형 대형 사이니지 콘텐츠를 위한 STAGCN 기반 인간 행동 인식 시스템)

  • Jeongho Kim;Byungsun Hwang;Jinwook Kim;Joonho Seon;Young Ghyu Sun;Jin Young Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.6
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    • pp.89-95
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    • 2023
  • In recent decades, human action recognition (HAR) has demonstrated potential applications in sports analysis, human-robot interaction, and large-scale signage content. In this paper, spatial temporal attention graph convolutional network (STAGCN)-based HAR system is proposed. Spatioal-temmporal features of skeleton sequences are assigned different weights by STAGCN, enabling the consideration of key joints and viewpoints. From simulation results, it has been shown that the performance of the proposed model can be improved in terms of classification accuracy in the NTU RGB+D dataset.

Shadow Removal in Front Projection System using a Depth Camera (깊이 카메라를 이용한 전방 프로젝션 환경에서 그림자 제거)

  • Kim, Jaedong;Seo, Hyunggoog;Cha, Seunghoon;Noh, Junyong
    • Journal of the Korea Computer Graphics Society
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    • v.21 no.3
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    • pp.1-10
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    • 2015
  • One way to create a visually immersive environment is to utilize a front projection system. Especially, when enough space is not available behind the screen, it becomes difficult to install a back projection system, making the front projection an appropriate choice. A drawback associated with the front projection is, however, the interference of shadow. The shadow can be cast on the screen when the user is located between the screen and the projector. This shadow can negatively affect the user experience and reduce the sense of immersion by removing important information. There have been various attempts to eliminating shadows cast on the screen by using multiple projectors that compensate for each other with missing information. There is trade-off between calculataion time and desired accuracy in this mutual compensation. Accurate estimation of the shadow usually requires heavy computation while simple approaches suffer from inclusion of non-shadow regions in the result. We propose a novel approach to removing shadows created in the front projection system using the skeleton data obtained from a depth camera. The skeleton data helps accurately extract the shape of the shadow that the user cast without requiring much computation. Our method also utilizes a distance field to remove the afterimage of shadow that may occur when the user moves. We verify the effectiveness of our system by performing various experiments in an interactive environment created by a front projection system.

Digital Signage service through Customer Behavior pattern analysis

  • Shin, Min-Chan;Park, Jun-Hee;Lee, Ji-Hoon;Moon, Nammee
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.9
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    • pp.53-62
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    • 2020
  • Product recommendation services that have been researched recently are only recommended through the customer's product purchase history. In this paper, we propose the digital signage service through customers' behavior pattern analysis that is recommending through not only purchase history, but also behavior pattern that customers take when choosing products. This service analyzes customer behavior patterns and extracts interests about products that are of practical interest. The service is learning extracted interest rate and customers' purchase history through the Wide & Deep model. Based on this learning method, the sparse vector of other products is predicted through the MF(Matrix Factorization). After derive the ranking of predicted product interest rate, this service uses the indoor signage that can interact with customers to expose the suitable advertisements. Through this proposed service, not only online, but also in an offline environment, it would be possible to grasp customers' interest information. Also, it will create a satisfactory purchasing environment by providing suitable advertisements to customers, not advertisements that advertisers randomly expose.