This document discusses gait recognition using infrared cameras. Gait recognition involves identifying individuals by the way they walk. Infrared cameras are used because they can extract human silhouettes regardless of lighting conditions. The gait recognition system first extracts features like height, width and area from infrared footage. These features are stored in a database. In the second phase, new footage is compared to the database to identify individuals. The system was tested on datasets with positive results, showing potential for applications like security and access control where gait recognition could identify threats or authorized individuals.

1. GAIT RECOGNITION
USING INFRARED

2. WHAT IS
GAIT ?
 Gait is a behavioral
characteristics of a person.
 Recognition using gait means to
identify a person by the way he
move or walk.
 Human gait recognition works
from the observation that an
individual’s walking style is unique
and can be used for human
identification.

3.  It is a smart surveillance systems from security-
sensitive areas
Eg :-
 Banks - To alert security officers to a suspicious
individual or unknown individual wandering about
the premises.
 Parking Lots
 Airports
WHERE CANWE
USETHESE
FEATURE?

4. Other than the individual, that cause variations in gait,
including
 Footwear
 Terrain
 Fatigue
 injury
 Muscle development
 Training
 Personal idiosyncrasies
Injury Footwear
Terrain Fatigue
CHALLENGE
S

5.  The camera is static and the only motion within
the field of view is that of the moving person
 The subject is monitored by multiple cameras so
that the subject presents a side view to at least
one of the cameras.
ASSUMPTIO
N

6. Unlike a regular camera which records reflected visible
light, a long wave infrared camera records electromagnetic
radiation emitted by objects in a scene. So, human silhouettes
can be easily extracted from the background regardless of
lighting conditions and colors of the human surfaces and
backgrounds
WHYWE USE
INFRARED?

7. FIRST PHASE OF GAIT
RECOGNITION SYSTEM
Store feature in
Database
Target
frame
CASIA
images

8. BACKGROUND
SUBTRACTION
Background Image Original Image Extracted boundary
box

9.  Mean Intensity
 Height , width
FEATURE
EXTRACTION
Height
Width
Detection of height
and width of a frame

10.  Area
 Centroid
FEATURE
EXTRACTION

11.  Diameter
FEATURE
EXTRACTION

12. CASIA
images
Yes
SECOND PHASE OF
GAIT RECOGNITION
SYSTEM
No

13. DATA SET

14. Experiment was performed on different
datasets. This dataset is divided into 2 set, first
contains the video sequences frame feature
and second contains CASIA database frames
features as shown in table.
Each contains the silhouette and extracted
features from different person’s walking
frame. Experiments performed on Matlab.
EXPERIMENT AND
RESULT

15. Gait recognition is one kind of biometric
technology that can be used to monitor
people without their cooperation.
Controlled environments such as banks,
military installations and even airports
need to be able to quickly detect threats
and provide differing levels of access to
different user groups.
CONCLUSI
ON

16.  Khan,H. Rathore,y., “Study and Analysis of Human Gait to
Recognize thePerson” ,”India”, vol.2, pp., 2013.
 Liang Wang, Tieniu Tan. Huazhong Ning. and Weiming Hu., “
Silhouette Analysis-Based Gait
Recognition for Human Identification” IEEE Transaction on
PAMI, Vol.25, pp 1505-1518, 2003.
 Shaveta Chauhan et al., “Review On: GAIT RECOGNITION
USING BPNN & SVM”, International Journal of Computer
Application and Technology, pp. 63-67 ,2014.
 Daehee Kim. Seungwon Lee. and Jooki Paik ., “Active Shape
Model-Based Gait Recognition Using Infrared Images”,” Image
Processing and Intelligent Systems Laboratory, Graduate
School of Advanced Imaging Science, Multimedia, and Film,
Chung-Ang University, 221 Heuksuk-Dong, Dongjak-Ku, Seoul
156-756, Korea”, Vol. 2 ,2009.
REFERENC
ES