Human Gait Recognition
Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
project report tiger
Active In SP

Posts: 1,062
Joined: Feb 2010
08-02-2010, 10:41 AM

.pdf   Human Gait Recognition.pdf (Size: 452.87 KB / Downloads: 167)


The reliable extraction of characteristic gait features from image sequences and their recognition are two important issues in gait recognition. In this paper, we propose a novel 2-step, model-based approach to gait recognition by employing a 5-link biped locomotion human model. We first extract the gait features from image sequences using the Metropolis-Hasting method. Hidden Markov Models are then trained based on the frequencies of these feature trajectories, from which recognition is performed. As it is entirely based on human gait, our approach is robust to different type of clothes the subjects wear. The model-based gait feature extraction step is insensitive to noise, cluttered background or even moving background. Furthermore, this approach also minimizes the size of the data required for recognition compared to model-free algorithms. We applied our method to both the USF Gait Challenge data-set and CMU MoBo data-set, and achieved recognition rate of 61% and 96%, respectively. The results suggest that the recognition rate is significantly limited by the distance of the subject to the camera. 1.

Presented By:
1Rong Zhang 2Christian Vogler 1Dimitris Metaxas
1 Department of Computer Science 2 Gallaudet Research Institute
Rutgers University Gallaudet University


Human recognition is an important task in a variety of applications, such as access control, surveillance, etc. To distinguish different persons by the manner they walk is a natural task people perform everyday. Psychological studies [10, 19] have showed that gait signatures obtained from video can be used as a reliable cue to identify individuals. These findings inspired researchers in computer vision to extract potential gait signatures from images to identify people. It is challenging, however, to find idiosyncratic gait features in marker-less motion sequences, where the use of markers is avoided because it is intrusive and not suitable in general gait recognition settings. Ideally, the recognition features extracted from images should be invariant to factors other than gait, such as color, texture, or type of clothing. In most gait recognition approaches [6, 16, 11], recognition features are extracted from silhouette images. Although these features are invariant to texture and color, the static human shape, which is easy to be concealed, inevitably mingles with the movement features In this paper, we propose a 2-step, model-based approach, in which reliable gait features are extracted by fitting a five-link biped human locomotion model for each image to avoid shape information, followed by recognition using Hidden Markov Models (HMMs) based on the frequency components of the trajectories of the relative joint positions. Applying our approach to both the USF Gait Challenge data-set and the CMU MoBo data-set, we demonstrate that promising recognition rate can be obtained using gait only features.

Important Note..!

If you are not satisfied with above reply ,..Please


So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page
Tagged Pages: usage of computer in human gait reconigtion, computer usage in human gait reconigtion, seminar topics for gait recognization, technical seminar on gait recognition, seminar report on gait recognition, review of hidden markov models based gait recognition, ppt human recognition by gait,
Popular Searches: gait biometrics seminar report, automatic gait recognition full report, seminar report for human gait recognition, gait recognition seminar report, locomotion fanpage, effective power point presentation, agent mobility effective teleservices,

Quick Reply
Type your reply to this message here.

Image Verification
Please enter the text contained within the image into the text box below it. This process is used to prevent automated spam bots.
Image Verification
(case insensitive)

Possibly Related Threads...
Thread Author Replies Views Last Post
  IRIS RECOGNITION pdf project girl 1 340 06-04-2016, 03:23 PM
Last Post: mkaasees
  Face Recognition-based Lecture Attendance System seminar tips 1 1,121 27-05-2015, 01:02 AM
Last Post: Guest
  eye movement based human computer interaction techniques ppt jaseelati 0 379 23-12-2014, 03:56 PM
Last Post: jaseelati
  CAR NUMBER PLATE RECOGNITION seminar girl 7 8,356 20-03-2014, 04:26 PM
Last Post: navasfiroz
  Improving ATM Security via Facial Recognition PPT seminar projects maker 0 525 25-09-2013, 02:30 PM
Last Post: seminar projects maker
  FACE RECOGNITION USING NEURAL NETWORKS (Download Seminar Report) Computer Science Clay 103 39,071 23-09-2013, 09:36 AM
Last Post: seminar projects maker
  Development of Indian Sign Language Recognition System PPT study tips 2 1,013 20-09-2013, 10:00 AM
Last Post: seminar projects maker
  Real-time Sign Language Recognition based on Neural Network Architecture study tips 0 512 24-08-2013, 04:35 PM
Last Post: study tips
  HUMAN COMPUTER EYE INTERFACE PPT study tips 0 366 13-07-2013, 12:34 PM
Last Post: study tips
  Improved Face Recognition Approaches for the Identification Purposes Report study tips 0 388 05-07-2013, 04:23 PM
Last Post: study tips