Core algorithm and main products by Junyu Tech.(China)
Core Algorithm & Main Products by Junyu Tech.(China)July , 2011
Contents Core Algorithm Main Products Our companyPage 2
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, 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.
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 backgroundVehicle license plate localization rate is not less than 97%.Recognition accuracy rate of fixed angle and size vehicle licenseplate is above 95%.Supports color and gray-scale images simultaneously.Supports 45 degrees of rolling angle.Supports geometric distortion within 15 degrees of vehicle licenseplate depth.Working with key algorithms of freground motion detection andvehicle 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.
On-line self-adaptation training algorithm Features TrainingCollect samples off-line Testing Distance Angle Test environment Normal classifier process of human body detection off-line training
On-line self-adaptation training algorithm Distance (Angle) Features Testing Collect samples off-line Training Angle Entelligent On-line Feature On-linesample expansion expansion training Test environment On-line learning strategy classifier process of human body detection training using on-line learning algorithm
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Face recognition softwareJohn 10:00Sales Department Lily 15:30 Marketing Dept. Annie 15:30 Paul 15:30 Marketing Dept. Marketing Dept.
Face recognition softwareFeatures: 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 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 Face pose detectionDozing detection Age &gender &smiling percentageLocal featureretrieval Face recognition
Pedestrian counting SDKFeatures: 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
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 systemFeatures: 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 systemReal application:
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Our companyJunyu Technology always focus on the research of imagerecognition and human biometric identification core technology,additionally works hard on the product application developmentand 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.
Rewards: Top 3 of FRVT2006Best Overall Performing Face Second Prize of National ScientificVerification Algorithm In the 2004 and Technological ProgressFace Authentication Test
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)
Thanks Louise Ye Wenying.firstname.lastname@example.orgWuxi Junyu Technology Co.,Ltd.(China) www.venpoo.com