Core algorithm and main products by Junyu Tech.(China)
35
July , 2011 Core Algorithm & Main Products by Junyu Tech.(China)
-
Upload
wuxi-junyu-technology-coltd-china -
Category
Technology
-
view
1.502 -
download
0
description
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".
Transcript of Core algorithm and main products by Junyu Tech.(China)
July , 2011
Core Algorithm & Main Productsby
Junyu Tech.(China)
Page 2
Core Algorithm
Contents
Main Products
Our company
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.
Multi-class object real-time detection algorithm under the complex background
Multi-class object real-time recognition algorithm
On the basis of acquiring the rough position of detecting target, JunyuTech. 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.
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.
Video-based object tracking and behavior analysis algorithm
Video-based object tracking and behavior analysis algorithm
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%.
Large-scale human face recognition and human face attribute analysis algorithm
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.
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.
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.
Collect samples off-line
Features
Training
Test environment
Distance
Angle
Normal classifier process of human body detection off-line training
Testing
On-line self-adaptation training algorithm
Collect samples off-line
Features
Training
Test environment
Distance
Angle
classifier process of human body detection trainingusing on-line learning algorithm
Testing
On-line learning strategy
EntelligentFeature
expansionOn-line
sample expansionOn-linetraining
(Angle)
On-line self-adaptation training algorithm
Page 16
Core Algorithm
Contents
Main Products
Our company
Face recognition softwareJohn 10:00Sales Department
Annie 15:30Marketing Dept. Paul 15:30
Marketing Dept.
Lily 15:30Marketing Dept.
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
Face recognition software
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.
Face recognition related SDKs
Age &gender&smiling percentage
Face pose detection
Face recognition
Dozing detection
Local featureretrieval
Pedestrian counting SDK (Human counting)
Real application:
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
Pedestrian counting SDK
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
Human body detection alarm system
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
Human body detection alarm system
Real application:
Page 29
Core Algorithm
Contents
Main Products
Our company
Our company
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.
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:
Rewards: Top 3 of FRVT2006
Best Overall Performing Face Verification Algorithm In the 2004 Face Authentication Test
Second Prize of National Scientific and Technological Progress
Tech. show on Global Sources Fair
Tech. show on Global Sources FairAge and gender and smiling percentage:
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)
