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300ms 92% Face Recognition Temperature Measurement Thermal Camera

Categories Temperature Measurement Thermal Camera
Brand Name: Kadymay
Model Number: KDM-FT8203EW
Certification: CE FCC
Place of Origin: China
MOQ: 50pcs
Price: USD648/pcs, Negotiated
Payment Terms: L/C, D/A, D/P, T/T, Western Union, MoneyGram
Supply Ability: 200per week
Delivery Time: 5-16
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300ms 92% Face Recognition Temperature Measurement Thermal Camera

Fever screening thermographic terminal
Temperature Measurement Face Recognition Algorithms Camera Thermal Camera SIlver Color

Introduction

Based on AR9201 AI chip, with the support of powerful computing power and face recognition algorithms, Our Fever Screening Thermographic Terminals are designed to detect elevated skin-surface temperatures, and can thus be used for rapid and preliminary fever screening in office buildings;new face recognition system for identify people wearing masks, granting access only to verified personnel and eliminating possible fraudulent activities.


Highlights

  • AI detection to reduce false alarms from other heat sources meet medical grade accuracy ±0.3 ℃
  • 300ms temperature detection for one person
  • New face recognition system for identify people wearing masks

Features
/ High sensitivity thermal module
l Measure forehead area only with AI face recognition algorithms
l Vanadium Oxide Uncooled Focal Plane Arrays
l 120*90 high resolution in thermal channel
l Temperature Distance: 0.3-1.5m
l Temperature Accuracy:±0.3 ℃
l Reliable fever detection alarm

/ Support face recognition with respirator

l Face recognize without removing their respirator
l Forehead temperature measurement within 100ms
l Recognition accuracy> 92%
l Real-time temperature abnormal alarm

/ Various door opening methods

l Multiple verfication methods: faces, cards and more
l RS485,TCP/IP interface

Specifications


SpecificationsKDM-FT8203EW
Thermal Module
Image SensorVanadium Oxide Uncooled Focal Plane Arrays
Thermal Iaging Pxels10000
Infrared Rsolution120*90@15fps
Temperature Distance0.3-1.5m
Temperature Accuracy±0.3 ℃
Hardware
processorAR9201
operating systemLinux
storage8GB EMMC+1G DDR4
LCD7 inches, 1024 * 600 resolution
Optical Module
Image Sensor2 million effective pixels, 1920 * 1080 SONY IMX
Signal to noise ratio≥50db(AGC OFF)
Wide dynamic range≥120dB
CameraDual cameras, 650nm and 850nm NIR

Face recognition
performance


Face Spoofing

Support Face Spoofing Detection Using Active
Near-Infrared Videos

Verfication height1.2 ~ 2.2 meters, adjustable angle
Faces capacity30000
Verfication distance0.3 ~ 2 meters, variable depending on the lens
Face angle30 degrees left and right, 30 degrees up and down
Interface
Alarm input2 alarm inputs
Alarm Output1 alarm output
power supplyDV12V
Network Interface1 RJ45 10M / 100M Ethernet port
1 *2.4G wifi module (optional)
1 *4G module (optional)
usb interface1 USB 2.0 interface
Wiegand interface1 pair Wiegand interface
Machine parameters
Operating temperatureOperating temperature: -40 ° c ~ + 60 ° c
PowerMaximum power <24w, 12v power supply
Dimensions120mm*226.5mm*33.5mm



Algorithm parameters

Scenes

Supported
algorithms

Description
Algorithm accuracy

Face recognition (1: 1):
99%@0.01% (accuracy rate is 99% under 0.01% false rate)
95%@0.0001% (95% accuracy under 0.0001% false
positive rate)

Angle requirementsYaw ± 30 degrees, roll ± 30 degrees, pitch ± 15 degrees
Face requirementsFace size is more than 80 * 80 pixels in images



Face live detection

Angle requirementsYaw ± 30 degrees, roll ± 30 degrees, pitch ± 15 degrees
Face requirementsFace size is more than 80 * 80 pixels in images
Algorithm accuracy

98%@0.01% (real person pass rate @false person pass
rate)

Non-living categoryNon-living detection for pictures, videos, coated paper, face fake models, etc.


Face detection and tracking

SnapshotsMore than 30 people / frame
Snapshot frame rate25fps
Smallest face30*30
Adaptation angleYaw ± 45 degrees, roll ± 45 degrees, pitch ± 30 degrees
Attribute contentGender, age, glasses, expression (angry, calm, happy, sad,


Face attribute recognition

surprised), mask, race, beard, race, hat detection, hard hat
detection





Algorithm accuracy

Age accuracy (± 5 years): more than 85%; Gender accuracy: 96% or more;
Skin tone accuracy: above 97%; Beard accuracy: above 97%; Glasses accuracy: more than 98%; Mask accuracy: more than 98%; Hat accuracy: above 97%;
Expression accuracy: 88% or more















































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