We develop face recognition software and other related SDKs and actually we are an algorithm provider. Our face recognition technology was awarded "TOP 3 of FRVT2006".

1. Core Algorithm & Main Products
by
Junyu Tech.(China)
July , 2011

2. Contents
Core Algorithm
Main Products
Our company
Page 2

3. Multi-class object real-time detection algorithm under
complex background
 Junyu Tech utilizes advanced machine learning and data mining
theory as a basic, to collect mass images and video demo off-line in
order to extract features after demarcating the samples artificially. As
a result, Junyu has designed efficient feature selection classifier via
the training which is based on eigenvalue and samples so make it
possible to do real-time detection and track multi-class objects under
complex background. E.g.The real-time detection of pedestrian, motor
vehicles and non-motorized vehicles in the intelligent traffic
monitoring system. And this algorithm can significantly improve
efficiency and save resources for following more elaborate target
segmentation recognition task.
 Advantage:
• Can detect multi-class objects simultaneously, such as human face,
human body, vehicle body, license plate and vehicle logo, traffic
signs, and other specified objects.
• The detection result is less affected by imaging perspective condition.
Can detect target object with different poses and angles.

4. Multi-class object real-time detection algorithm
under the complex background

5. Multi-class object real-time recognition algorithm
 On the basis of acquiring the rough position of detecting target, Junyu
Tech. has researched the object real-time segmentation recognition
algorithm both based on model and non-based on model which are
used separately according to different background to acquire accurate
information of the difference between target object and background
and other objects such as pedestrian aspect, vehicle types etc. So as
to achieve the target object recognition therefore provide effective
object information for following motion tracking.
 Among this algorithm, accurate information acquiring is not relied on
off-line training thus this algorithm has wide application area and less
limitation by environment.

6. Video-based object tracking and behavior analysis
algorithm
 Based on aggregate category statistical analysis, Junyu Tech. has
researched video-based object tracking and behavior analysis
algorithm according to the specific target in the tracking video. This
algorithm takes accurate information of target object acquired via
multi-class object real-time segmentation and recognition algorithms
as a input, using the unique algorithm of target object accurate
information analysis and motion target tracking, to track the specific
target e.g. pedestrian and vehicles.
 This algorithm can be used in calculating the motion track and
counting the number of target object which has been successfully
applied in our products of vehicle and pedestrian counting.
 This algorithm also includes behavior analysis module which can
recognize the target object’s behavior, for example, sitting, standing,
running, climbing or pounding. The application can cover the security
surveillance of crowded environment such as prisons or station
waiting halls.

7. Video-based object tracking and behavior analysis
algorithm

8. Video-based object tracking and behavior analysis
algorithm

9. Large-scale human face recognition and human
face attribute analysis algorithm
 Based on the advanced machine learning algorithm and eigenvalue extracting
methodology, Junyu Tech. has researched human face recognition and human
face attribute analysis algorithm both are appropriate for mass data.
 During the research process of this algorithm, Junyu has been collecting mass
data against human face, including various poses, various light conditions,
human face image of large age span therefore this algorithm has the features
of strong adaptation of posture, low requirement of light conditions, high
accuracy among mass database and good real-time performance：
 Real-time performance: recognition speed is less than 1s among million human face database.
 Accuracy: the top one correct rate is not less than 90% among million human face database.
 Posture adaptation: human face can yaw within -30 degrees to +30 degrees, can pitch within -15
degrees to +15 degrees.
 Light conditions requirement: the light on human face can not be lower than 4lux( non-night is
ok)
 This algorithm also includes human face attribute analysis module which can
recognize age, gender, expression judgment and wearing glass or not. Among
it, the age gap is not above 5, age accuracy is not less than 96%, gender
accuracy is not less than 97%.

10. Large-scale human face recognition and human
face attribute analysis algorithm

11. Text localization and recognition algorithm under
complex background
 Text information is an important visual clue in security
surveillance. Based on the text structure information and via
mining of broad category & large number sample statistical
distribution rule, Junyu has developed a high-performance text
localization and OCR engine under complicated background.
The engine can accurately localize and recognize text including
Arabic number, English and GB-I and GB-II Chinese characters.
 This algorithm has been successfully applied in vehicle license
plate recognition, content-based image retrieval products of
our company.

12. Text localization and recognition algorithm under
complex background
Vehicle license plate localization rate is not less than 97%.
Recognition accuracy rate of fixed angle and size vehicle license
plate is above 95%.
Supports color and gray-scale images simultaneously.
Supports 45 degrees of rolling angle.
Supports geometric distortion within 15 degrees of vehicle license
plate depth.
Working with key algorithms of freground motion detection and
vehicle body detection, can absolutely reduce the rate of false report.

13. On-line self-adaptation training algorithm
 Because light conditions and angle information in real application environment
are not available beforehand during the off-line training stage, the performance
of off-line learned parameters is not optimum for the real environment. Under
such circumstances, Junyu has developed on-line self-adaptation training
algorithm. This algorithm can adapt by itself to adjust off-line learned
parameters according to the feedback from on-line environment thus improve
object detection rate and action recognition rate.
 This algorithm has been widely applied in various products of our company to
increase object detection rate and action recognition rate.

14. On-line self-adaptation training algorithm
Features
Training
Collect samples off-line
Testing
Distance
Angle
Test environment
Normal classifier process of
human body detection off-line training

15. On-line self-adaptation training algorithm
Distance
(Angle)
Features
Testing
Collect samples off-line
Training
Angle
Entelligent
On-line Feature On-line
sample expansion expansion training
Test environment
On-line learning strategy
classifier process of human body detection training
using on-line learning algorithm

16. Contents
Core Algorithm
Main Products
Our company
Page 16

17. Face recognition software
John 10:00
Sales Department
Lily 15:30
Marketing Dept.
Annie 15:30
Paul 15:30
Marketing Dept.
Marketing Dept.

18. Face recognition software
Features:
 Can recognize the face in any angle of rotation, in angle of
yawing within [-30,30] degrees, pitching within [-15,15]
degrees.
 Can be at the best performance with the light condition which
is under control
 Not influenced by the skin color, proper make up or glasses
etc.
 The minimum face detection size: 24 pixels
 The minimum face recognition size: 48 pixels

19. Face recognition software

20. Face recognition related SDKs
 Multi-View Face Detection Module
-Real time detect the rough poses of faces in input video/image
 Face Pose Estimation module
-Estimate face pose (pitch, roll, yaw) for the given faces
 Key Facial Points Localization Module
-Localize key facial points in the given rough face area including
two eye centers, eye corners, nose tip, mouth center, etc.
 Eye gaze/Eye opening degree estimation module
-Estimate gaze direction, eye opening degree based on the above
rough positions of faces.
 Age and gender and smiling percentage estimation module
-Estimate age, gender and smiling percentage for the given faces
 Face local feature retrieval system
- Retrieval the similar face local feature in the database.

21. Face recognition related SDKs
Face pose
detection
Dozing detection
Age &gender
&smiling
percentage
Local feature
retrieval
Face recognition

22. Pedestrian counting SDK (Human counting)
Real application:

23. Pedestrian counting SDK
Features:
 Advanced technology: developed under the technology of human
body detection, video-based object tracking, freground detection.
 Accurate statistics: average accuracy is above 92%, and above 85% at
time of rush hour. The detection is less affected by the high-density
population and people’s complicated behavior.
 Can achieve the counting precision over 95% on our evaluation sets.
 Different directions statistics: Two-way statistics for customer in and
out, can recognize 8 directions of customer flow simultaneously.
 Can process VGA video at the speed of 15 fps on PC platform (Dual 2
CPU 2.0GHZ) and detect/track 30 persons simultaneously
 Can attain the speed of 8 fps on TMS320C DSP chips

24. Pedestrian counting SDK

25. Human body detection alarm system
(SDK or Hardware)
Function:
 Human body detection and motion tracking over a certain period of
time and area
 Take scene picture, send MMS to owner, instant phone call to owner
as an alarm
 Early warning alarm bell which is deterrent to criminals
 Support the connection with “911” police center and the estate
management to achieve successful alarm linkage

26. Human body detection alarm system

27. Human body detection alarm system
Features:
 The world’s leading technology: human body detection ,
motion tracking and freground detection
 Embedded software
 Initiatively & Instantly: initiative early warning and instant
informing
 Low rate of false report: strong ability of anti-interference, rate
of false report is less than 1‰
 Day and night monitoring: real-time surveillance under any
light conditions
 No need of auxiliary equipment, easy operation by mobile
phone

28. Human body detection alarm system
Real application:

29. Contents
Core Algorithm
Main Products
Our company
Page 29

30. Our company
Junyu Technology always focus on the research of image
recognition and human biometric identification core technology,
additionally works hard on the product application development
and marketing promotion.
Junyu’s research includes:
 Face recognition, face attribute analysis(age & gender and
more)
 Detection, recognition, counting and behavior analysis of
human body and vehicle body
 Motion tracking
 Character recognition
 Analyzing recognition of medical imaging
 Content-based image and video retrieval etc.

31. Rewards: Top 3 of FRVT2006
Best Overall Performing Face Second Prize of National Scientific
Verification Algorithm In the 2004 and Technological Progress
Face Authentication Test

32. Tech. show on Global Sources Fair

33. Tech. show on Global Sources Fair
Age and gender and smiling percentage:

34. Our professional team
 Our core professional engineers each has more than 10 years
research and development experience in the area of object
tracking recognition as well as successful business application
experience.
 Have published several professional articles on the top global
academic conferences or journals in the area of machine
learning, artificial intelligence, computer vision etc.
 The management team has degrees of :
• Doctor’s degree of Tsinghua University (Top 3 in China)
• Master’s degree of University of British Lan Caster
• MBA degree of Fudan University(Top 3 in China)

35. Thanks
Louise Ye
Wenying.ye@venpoo.com
Wuxi Junyu Technology Co.,Ltd.(China)
www.venpoo.com