1. BIOMETRICS: GAIT RECOGNITION
BY:
Tarun Mehrotra
M.Tech(IT-12MCMB11)

2. CONTENTS Overview of Biometrics Biometrics: Gait Recognition
Categorization of approaches in Gait recognition (Features and Applications)
Comparison of approaches
Combining Gait with other biometrics
References

3. Overview of Biometrics
"Biometric" comes from the Greek words "bio" (life) and "metric" (to measure).
Used for measuring and analyzing a person's unique characteristics.
Biometrics are used for identification and verification.
Identification: determining who a person is.
Verification: determining if a person is who
they say they are.

4. Types of Biometrics
There are two types of biometrics: Behavioral and Physical.
Behavioral:
Voice recognition, keystroke, gait recognition (manner of walking), signature .
Physical:
Fingerprint, retina, hand, face.
Other biometric techniques, still in exploratory stages would include DNA biometrics, ear shape, fingernails or odor.

5. GAIT RECOGNITION

6. WHAT IS GAIT RECOGNITION ?
Gait recognition is recognising people based on the way they walk.
The interest in gait as a biometric is strongly motivated by the need for an :
automated recognition system for visual surveillance and
monitoring applications.

7. CATEGORIZATION OF APPROACHES IN GAIT RECOGNITION
BIOMETRIC GAIT RECOGNITION APPROACHES
MACHINE VISION
(MV)
WEARABLE SENSOR
(WS)
FLOOR SENSOR
(FS)

8. MACHINE VISION(MV)-BASED
Gait captured using video camera from distance.
Video and Image processing techniques are employed to extract gait features for recognition purposes.
Most of algos are based on HUMAN SILHOUETTE.
( image of a person represented as a solid shape of a single color, usually black, its edges matching the outline of the subject.)

9. Silhouette Images

10. General block diagram of a gait recognition system

11. EXTRACTION OF SILHOUETEE
Image Background is removed
Silhouette is extracted & analysed for recognition.

12. ADVANTAGES OF MV BASED
UNOBTRUSIVENESS ,i.e it can be capture at a distance & without requiring prior consent of the observed subject.
Machine vision can be used for access control, surveillance, detection and monitoring purposes.

13. Applications Mostly used for: Surveillance Forensics Example:
In bank robbery case in Denmark, a court found Gait analysis from video a valuable tool.

14. Floor Sensor(FS)-based Gait recognition
Set of sensors or force plates are installed on the floor.
Such sensors enable to measure gait related features when person walks on them.
Use of floor sensors for studying the way we walk is commonly employed by physiologists.
Pathological gait is a key indicator of several age related diseases such as Diabetic Polyneuropathy.

15. SENSORS (FS-Based)
A prototype sensor mat
A prototype sensor mat

16. Advantage and Deployment
The FS-based gait recognition can be deployed in access control application and is usually installed in front of doors in the building.
One of the main advantages of FS-based gait recognition is in its unobtrusive data collection.
In addition to providing identity information, the FS-based gait system can also indicate location information within a building

17. WEARABLE SENSOR(WS)-BASED
WS-based gait recognition is relatively recent compared to the other two mentioned approaches.
Motion recording sensors are worn or attached to various places on the body of the person.
The movement signal recorded by such sensors is then utilized for person recognition purposes.
Main research is on identifying several body parts whose motion can provide some identity information during gait.

18. Motion Recording Sensors

19. Placement of MRS on Body

20. Application of WS-Based
Using small,low-power, and low-cost sensors it can enable a periodic (dynamic) reverification of user identity in personal electronics.
An important aspect of periodic identity reverification is unobtrusiveness, not to distract user attention, and to be user friendly and convenient in frequent use.
As we make a few steps ,our identity is re-verified in background by MRS.

21. APPLICATIONS (Contd.)
Approach was proposed for protection and user authentication in mobile and portable devices.
Besides the mobile phones , the motion recording/detecting sensors can be found in a wide range of other consumer electronics, gadgets, and clothes etc.
(i) laptops use accelerometer sensors for drop protection of their hard drive
(ii) various intelligent shoes with integrated sensors are developed etc.

22. GAIT SIGNATURE CREATION
1)Each frame of video feet is processed. 2)Silhouette is extracted. 3)Gait cycles are generated . 4)Cycles generates set of numbers. 5)Every time person walks they represent similar set of numbers which can be used for recognition. 6)Ultimately security systems can be made that combine Real Time Video to Automated Biometric Recognition.

23. COMPARISON METHODS OF GAIT RECOGNITION RECOGNITION FEATURES
PERFORMANCE ACHIEVED (in %)
MACHINE-VISION BASED
Static body parameters : Height, distance between head & limbs , distance between feet etc. 95
FLOOR-VISION BASED
Max. Time value of heel strike , max amplitude value of heel strike etc. 80
WEARABLE-SENSOR BASED
MR sensors attached on different parts of body like shoe , waist, hand etc.
86.3

24. Challenges of Gait recognition
Performance is encouraging , but some factors negatively influence accuracy of such approach.
Factors
External
(Challenges to recognition)
Viewing angles
Lightning conditions
Outdoor/Indoor environment
Etc.
Internal
(Changes to natural Gait)
Due to sickness
Due to aging
Gaining or losing weight

25. Combining Gait with other Biometrics
Multi Modal Biometric System:
Multimodal biometrics use a combination of different biometric recognition technologies.
Gait helps in improving the accuracy of the system when it is integrated with other biometrics.
Provide improved security.
More robust against attacks.

26. REFERENCES
A Survey of Biometric Gait Recognition:Approaches, Security and Challenge( NIK-2007 conference): Davrondzhon Gafurov. (Gjøvik University College,Norway)
Nikolaos V. Boulgouris, Dimitrios Hatzinakos,and Konstantinos N.Plataniotis (IEEE SIGNAL PROCESSING MAGAZINE, NOVEMBER 2005) :GAIT RECOGNITION:A challening signal processing technology for Biometric identification.
Ravi Das,( Keesing Journal of Documents & Identity, issue 25, 2008 ): Biometric Technologies of the future.
G. Venkata Narasimhulu, Dr. S. A. K. Jilani. Gait Recognition : A Survey, Volume 3, Issue 1, ISSN: 2249 –071X.

27. THANK YOU