Junyu Tech is a Chinese company that develops face recognition software and related SDKs. The document describes Junyu Tech's face recognition principles, performance testing results, applications, and additional modules. It also provides details on Junyu Tech's patents, professional team, and participation in tech shows.

1. Face Recognition Software
by
Junyu Tech. (China)
August , 2011

2. Contents
Face recognition software
More SDKs related to face recognition
Our company
Page 2

3. Face recognition: software principle
 Via uploading local picture of PC or capturing picture by
camera, face recognition software can recognize who the
person is by automatic eigenvalue comparison between the
pictures of both uploading and human face database.

4. Face recognition: software Interface

5. Face recognition: software system components
 Human face database
 Face recognition SDK
 Camera
 Server Face recognition software
 Client terminal system
Face
Human face database recognition
SDK
Client
Camera Server
terminal

6. Face recognition: software configuration diagram

7. Face recognition: software performance
 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
wearing etc.
 The minimum face detection size: 24 pixels
 The minimum face recognition size: 48 pixels

8. Face recognition: detection angle range
Yaw Pitch +30
+15
－9０ 9０
-15
－５０ +５０
－３０
+３０
－30
－１０ +１０
 Yaw within [-30,30] degrees
Roll
 Pitch within [-15,15] degrees
 Roll in any angle
+

9. Face recognition: software test report
With the cooperation of Wuxi municipal public security bureau, the test has
covered 3.94 million citizens.
Picture Sample First Former Former Former
Test scale
type size hit 30 100 200
Police Full pool 72% 88% 92% 92%
certificate 36
photo Designated age 72% 100% 100% 100%
Full pool 15% 19% 22% 48%
27
Detention
Designated age 15% 59% 67% 85%
officer photo
Full pool 4% 19% 28% 38%
Internet café
52
photo
Designated age 6% 42% 61% 75%
Note: the designated age scale is -10 to10. It is 20 year age scale.

10. Face recognition: more testing data
With the cooperation of Wuxi municipal public security bureau,
the test has covered 3.94 million citizens. Another test with
Shaoxin municipal public security bureau has covered 4 million
citizens:
 The first hit rate of ID card photo is 100%, similarity reached
93%.
 The first hit rate of certificate photo is 72%, former 100 hit rate
is 100%.
Top 3 of FRVT2006 :
 Among million database, the first hit rate of certificate photo
reached not less than 92%, former 30 hit rate reached not less
than 98%.

11. Face recognition: areas of application
 Public security system.
 Building access control system.
 Working staff attendance surveillance system
 Shopping mall customer analysis
 Banking environment application
 Intelligent kids dolls
 More specific business applications

12. Face recognition: application example
John 10:00
Sales Department
Lily 15:30
Marketing Dept.
Annie 15:30
Paul 15:30
Marketing Dept.
Marketing Dept.

13. Contents
Face recognition software
More SDKs related to face recognition
Our company
Page 13

14. More SDKs related to face recognition
 Multi-view face detection
 Face pose estimation
 Key facial points localization
 Eye gaze/eye opening degree estimation
 Age and gender and smiling percentage estimation
 Face local feature retrieval system

15. More SDKs related to face recognition:
SDK description
 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.

16. Multi-view face detection：performance
 Can detect faces pitch within [-45,45] degrees, yaw within
[-90, 90] degrees, and roll within [-45,45] degrees;
 Can detect minimum face size of 30 pixels
 Can detect faces in VGA video at the speed of 20fps (on PIV
3GHZ CPU, at most 5 persons at the same time) without any
tracking techniques
 Can achieve excellent detection rate with very low false
alarm rate (<10e-7) on CMU Frontal test set A, B, profile test
set.

17. Face pose estimation: performance
 Can estimate faces pitch within [-30,30] degrees, and yaw
within [-90, 90] degrees
 Pose estimation correct rate is over 94% with the error within
10 degrees
 Speed is over 50 fps (on PIV 3GHZ CPU)

18. Key facial points localization: performance
 Can accurately localize over 10 key facial points of faces
pitch within [-30,30] degrees, and yaw within [-60, 60]
degrees
 Key facial points include left/right eye center, inner/outer
corner, nose tip, mouth center/corner etc.
 Speed is over 30 fps (on PIV 3GHZ CPU)

19. Eye gaze/eye opening degree estimation:
performance
 Can estimate faces pitch within [-30,30] degrees, and yaw
within [-60, 60] degrees.
 Correct rate of eye gaze direction estimation is over 90% with
error within 10 degrees.
 Speed: 50fps (PIV 3GHz)
Dozing detection
(Fatigue driving
detection)

20. Age and gender and smiling percentage
estimation: performance
 Correct rate of age is over 90% with possible error within [-5,5]
years old.
 Correct rate of gender can achieve 96% for people among 7 to
70 years old.
 Until now we only have done the off-line training for Asian
people.

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

22. Contents
Face recognition software
More modules related to face recognition
Our company
Page 22

23. 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.

24. Our company(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

25. Our company: patents
8 patents on utility have been obtained:
 One child shuttle processing device based on face recognition
 One processing device based on face recognition and vivo
identification
 One monitoring device which can automatically track the scene
of crowded people
 One living body detecting device used on flying object
 One online self-service certificate applying processing device
 One monitoring device for advertisement effectiveness
assessment
 One switching device of TV mode based on human eye feature
analysis
 One device of that existingvideo image matches the kara ok
melody in real-time

26. Our company: patents
4 patents on invention have been obtained:
 One traffic violation detection method based on video-base
object tracking and pattern recognition
 One age assessment method based on face recognition
 One queuing up time assessment method based on vision.
 One human face information automatic login method based on
human face recognition technology

27. Our company: Tech. show on Global Sources Fair

28. Our company: tech. show on Global Sources Fair
Age and gender and smiling percentage:

29. Our company: our professional team
 Our main 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)

30. Thanks
Louise Ye
Twitter: @LouiseYe93
Email: Wenying.ye@venpoo.com
Wuxi Junyu Technology Co.,Ltd.(China)
www.venpoo.com