Temperature Measuring Face Recognition

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Temperature Measuring Face Recognition

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About this item
  • Support camera to capture face to activate device;
  • Human body temperature detection using thermal imaging; with access control attendance function;
  • Automatic alarm when human body temperature is higher than 37.3 (customizable temperature value);
  • Using RGB and living body dynamic binocular camera;
  • Supports serial port, Wigan 26, 34 input and output;
  • Using video stream-based dynamic face detection,tracking recognition algorithm;
  • Support device local storage of 10,000 face libraries;
  • When the face database is 3,000 , misrecognition rate is 3 in 10,000, 1: N recognition accuracy rate is 99.7%;
  • Fast recognition speed: (a) face tracking and detection takes about 20ms, (b) face feature extraction takes about 200ms, (c) face comparison takes about 0.2ms(1000 people database, multiple identification to get the average), 0.5ms(10,000 face database,multiple identification to get the average);
  • Binocular with infrared light camera;
  • Support live photo saving during face recognition or stranger detection;
  • Support HTTP Interface connection;
  • Support public network and local area network deployment;

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Temperature Measuring Face Recognition

  • Support camera to capture face to activate device;
  • Human body temperature detection using thermal imaging; with access control attendance function;
  • Automatic alarm when human body temperature is higher than 37.3 (customizable temperature value);
  • Using RGB and living body dynamic binocular camera;
  • Supports serial port, Wigan 26, 34 input and output;
  • Using video stream-based dynamic face detection,tracking recognition algorithm;
  • Support device local storage of 10,000 face libraries;
  • When the face database is 3,000 , misrecognition rate is 3 in 10,000, 1: N recognition accuracy rate is 99.7%;
  • Fast recognition speed: (a) face tracking and detection takes about 20ms, (b) face feature extraction takes about 200ms, (c) face comparison takes about 0.2ms(1000 people database, multiple identification to get the average), 0.5ms(10,000 face database,multiple identification to get the average);
  • Binocular with infrared light camera;
  • Support live photo saving during face recognition or stranger detection;
  • Support HTTP Interface connection;
  • Support public network and local area network deployment;

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