• Title, Summary, Keyword: Gait recognition

Search Result 69, Processing Time 0.039 seconds

Analysis on Dominant Factor for Gait Recognition (걸음걸이 인식을 위한 지배 요소 분석)

  • 박한훈;박종일
    • Proceedings of the IEEK Conference
    • /
    • /
    • pp.321-324
    • /
    • 2003
  • This paper presents a novel system that analyzes and recognizes a gait based on shape context on silhouette images. The main functions of the system consist of three steps: First, the system extracts the silhouette images from galt image sequence by performing a simple pre-processing and acquires the AGM(Averaged Gait Map) by averaging them. Next. it computes the cross-correlation between the AGMs. Finally, it classifies the AGMs based on the cross-correlation using nearest neighborhood classification. The proposed system uses two cues to classify a gait: One corresponds to biometric shape cue such as body height width. and body-part proportions. The other corresponds to gait cue such as stride length and amount of arm swing. Perceptionally, the biometric cues are sailent on the double support (both legs spread and touching the ground) while the gait cues on the midstance. Through a variety of experiments, it is proved that the property of a gait is mainly influenced by gait cues than biometric cues.

  • PDF

Fusion algorithm for Integrated Face and Gait Identification (얼굴과 발걸음을 결합한 인식)

  • Nizami, Imran Fareed;An, Sung-Je;Hong, Sung-Jun;Lee, Hee-Sung;Kim, Eun-Tai;Park, Mig-Non
    • Journal of Korean Institute of Intelligent Systems
    • /
    • v.18 no.1
    • /
    • pp.72-77
    • /
    • 2008
  • Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion in considered at decision level. The proposed algorithm is tested on the NLPR database.

Statistical Modeling Methods for Analyzing Human Gait Structure (휴먼 보행 동작 구조 분석을 위한 통계적 모델링 방법)

  • Sin, Bong Kee
    • Smart Media Journal
    • /
    • v.1 no.2
    • /
    • pp.12-22
    • /
    • 2012
  • Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

  • PDF

Gate Data Gathering in WiFi-embedded Smart Shoes with Gyro and Acceleration Sensor

  • Jeong, KiMin;Lee, Kyung-chang
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.22 no.4
    • /
    • pp.459-465
    • /
    • 2019
  • There is an increasing interest in health and research on methods for measuring human body information. The importance of continuously observing information such as the step change and the walking speed is increasing. At a person's gait, information about the disease and the currently weakened area can be known. In this paper, gait is measured using wearable walking module built in shoes. We want to make continuous measurement possible by simplifying gait measurement method. This module is designed to receive information of gyro sensor and acceleration sensor. The designed module is capable of WiFi communication and the collected walking information is stored in the server. The information stored in the server is corrected by integrating the acceleration sensor and the gyro sensor value. A band-pass filter was used to reduce the error. This data is categorized by the Gait Finder into walking and waiting states. When walking, each step is divided and stored separately for analysis.

A study for semi-static quadruped walking robot using wave gait (물결걸음새를 이용한 준정적 4족 보행로봇에 관한 연구)

  • 최기훈;김태형;유재명;김영탁
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • /
    • pp.551-554
    • /
    • 2001
  • A necessity of remote control robots or various searching robots etc. that accomplish works given instead of human under long distance and extreme environment such as volcano, universe, deep-sea exploration and nuclear power plant etc. is increasing, and so the development and the research regarding these mobile robots are actively progressing. The wheel mobile robot or the track mobile robot have a sufficient energy efficiency under this en, but also have a lot of limits to accomplish works given which are caused from the restriction of mobile ability. Therefore, recently many researches for the walking robot with superior mobility and energy efficiency on the terrain, which is uneven or where obstacles, inclination and stairways exist, have been doing. The research for these walking robots is separated into fields of mechanism and control system, gait research, circumference environment and system condition recognition etc. greatly. It is a research field that the gait research among these is the centralist in actual implementation of walking robot unlike different mobile robots. A research field for gait of walking robot is classified into two parts according to the nature of the stability and the walking speed, static gait or dynamic gait. While the speed of a static gait is lower than that of a dynamic gait, a static gait which moves the robot to maintain a static stability guarantees a superior stability relatively. A dynamic gait, which make the robot walk controlling the instability caused by the gravity during the two leg supporting period and so maintaining the stability of the robot body spontaneously, is suitable for high speed walking but has a relatively low stability and a difficulty in implementation compared with a static gait. The quadruped walking robot has a strong point that can embody these gaits together. In this research, we will develope an autonomous quadruped robot with an asaptibility to the environment by selectry appropriate gait, element such as duty factor, stride, trajectory, etc.

  • PDF

Method of Walking Surface Identification Technique for Automatic Change of Walking Mode of Intelligent Bionic Leg (지능형 의족의 보행모드 자동변경을 위한 보행노면 판별 기법)

  • Yoo, Seong-Bong;Lim, Young-Kwang;Eom, Su-Hong;Lee, Eung-Hyuk
    • Journal of rehabilitation welfare engineering & assistive technology
    • /
    • v.11 no.1
    • /
    • pp.81-89
    • /
    • 2017
  • In this paper, we propose a gait pattern recognition method for intelligent prosthesis that enables walking in various environments of femoral amputees. The proposed gait mode changing method is a single sensor based algorithm which can discriminate gait surface and gait phase using only strain gauges sensor, and it is designed to simplify the algorithm based on multiple sensors of existing intelligent prosthesis and to reduce cost of prosthesis system. For the recognition algorithm, we analyzed characteristics of the ground reaction force generated during gait of normal person and defined gait step segmentation and gait detection condition, A gait analyzer was constructed for the gait experiment in the environment similar to the femoral amputee. The validity of the paper was verified through the defined detection conditions and fabricated instruments. The accuracy of the algorithm based on the single sensor was 95%. Based on the proposed single sensor-based algorithm, it is considered that the intelligent prosthesis system can be made inexpensive, and the user can directly grasp the state of the walking surface and shift the walking mode. It is confirmed that it is possible to change the automatic walking mode to switch the walking mode that is suitable for the walking mode.

Gait-Event Detection using an Accelerometer for the Paralyzed Patients (가속도계를 이용한 마비환자의 보행이벤트 검출)

  • Kong, Se-Jin;Kim, Chul-Seung;Moon, Ki-Wook;Eom, Gwang-Moon;Tack, Gye-Rae;Kim, Kyeong-Seop;Lee, Jeong-Whan;Lee, Young-Hee
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.56 no.5
    • /
    • pp.990-992
    • /
    • 2007
  • The purpose of this study is to develop a practical gait-event detection system which is necessary for the FES (functional electrical stimulation) control of locomotion in paralyzed patients. The system is comprised of a sensor board and an event recognition algorithm. We focused on the practicality improvement of the system through 1) using accelerometer to get the angle of shank and dispensing with the foot-switches having limitation in indoor or barefoot usage and 2) using a rule-base instead of threshold to determine the heel-off/heel-strike events corresponding the stimulation on/off timing. The sensor signals are transmitted through RF communication and gait-events was detected using the peaks in shank angle. The system could detect two critical gait-events in all five paralyzed patients. The standard deviation of the gait events time from the peaks were smaller when 1.5Hz cutoff frequency was used in the derivation of the shank angle from the acceleration signals.

Gait Phase Recognition based on EMG Signal for Stairs Ascending and Stairs Descending (상·하향 계단보행을 위한 근전도 신호 기반 보행단계 인식)

  • Lee, Mi-Ran;Ryu, Jae-Hwan;Kim, Sang-Ho;Kim, Deok-Hwan
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.52 no.3
    • /
    • pp.181-189
    • /
    • 2015
  • Powered prosthesis is used to assist walking of people with an amputated lower limb and/or weak leg strength. The accurate gait phase classification is indispensable in smooth movement control of the powered prosthesis. In previous gait phase classification using physical sensors, there is limitation that powered prosthesis should be simulated as same as the speed of training process. Therefore, we propose EMG signal based gait phase recognition method to classify stairs ascending and stairs descending into four steps without using physical sensors, respectively. RMS, VAR, MAV, SSC, ZC, WAMP features are extracted from EMG signal data and LDA(Linear Discriminant Analysis) classifier is used. In the training process, the AHRS sensor produces various ranges of walking steps according to the change of knee angles. The experimental results show that the average accuracies of the proposed method are about 85.6% in stairs ascending and 69.5% in stairs descending whereas those of preliminary studies are about 58.5% in stairs ascending and 35.3% in stairs descending. In addition, we can analyze the average recognition ratio of each gait step with respect to the individual muscle.

A General Representation of Motion Silhouette Image: Generic Motion Silhouette Image(GMSI) (움직임 실루엣 영상의 일반적인 표현 방식에 대한 연구)

  • Hong, Sung-Jun;Lee, Hee-Sung;Kim, Eun-Tai
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.13 no.8
    • /
    • pp.749-753
    • /
    • 2007
  • In this paper, a generalized version of the Motion Silhouette Image(MSI) called the Generic Motion Silhouette Image (GMSI) is proposed for gait recognition. The GMSI is a gray-level image and involves the spatiotemporal information of individual motion. The GMSI not only generalizes the MSI but also reflects a flexible feature of a gait sequence. Along with the GMSI, we use the Principal Component Analysis(PCA) to reduce the dimensionality of the GMSI and the Nearest Neighbor(NN) for classification. We apply the proposed feature to NLPR database and compare it with the conventional MSI. Experimental results show the effectiveness of the GMSI.

Gait Recognition using Modified Motion Silhouette Image (개선된 움직임 실루엣 영상을 이용한 발걸음 인식에 관한 연구)

  • Hong Seong-Jun;Lee Hui-Seong;O Gyeong-Se;Kim Eun-Tae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • /
    • pp.49-52
    • /
    • 2006
  • 본 논문에서는 은닉 마르코프 모델을 바탕으로 하는 발걸음을 이용한 개인 식별 시스템을 제안한다. 개인의 발걸음은 연속적인 자세나 움직임의 집합으로 나타낼 수 있는데, 구조적으로 연속적인 움직임의 변화는 확률적인 특성을 가지고 있기 때문에 은닉 마르코프 모델을 이용하여 적절하게 모델링 할 수 있다. 개인의 발걸음은 N개의 이산적인 자세 간의 전이로 이루어졌다고 가정하였으며, 이를 계산하기 위해 MMSI라는 발걸음 특징 모델을 제안하였다. MMSI는 발걸음 인식에 중요한 역할을 하는 시공간적인 정보를 가지고 있는 그레이-스케일 영상이다. 실험 결과는 MMSI를 이용하여 은닉 마르코프 모델을 바탕으로 한 발걸음 인식 결과를 보여준다.

  • PDF