18464257. CONTROL APPARATUS, CONTROL METHOD, AND PROGRAM simplified abstract (FUJIFILM Corporation)

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CONTROL APPARATUS, CONTROL METHOD, AND PROGRAM

Organization Name

FUJIFILM Corporation

Inventor(s)

Tomoharu Shimada of Saitama-shi (JP)

Masahiko Sugimoto of Saitama-shi (JP)

Tetsuya Fujikawa of Saitama-shi (JP)

CONTROL APPARATUS, CONTROL METHOD, AND PROGRAM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18464257 titled 'CONTROL APPARATUS, CONTROL METHOD, AND PROGRAM

Simplified Explanation

The patent application describes a control apparatus for a surveillance camera that uses machine learning to detect objects and adjust the imaging range accordingly. Here are the key points:

  • The control apparatus includes a processor that controls a surveillance camera.
  • It enables switching between a first surveillance mode and a second surveillance mode.
  • In the first mode, the camera acquires a first captured image and the imaging range can be changed based on instructions.
  • In the second mode, the camera acquires a second captured image and a trained model is used to detect objects in this image.
  • The imaging range is adjusted based on the detection result from the trained model.
  • The first captured image acquired in the first mode is used as a teacher image for machine learning.

Potential applications of this technology:

  • Surveillance systems in public places, such as airports, train stations, and shopping malls.
  • Security systems in residential and commercial buildings.
  • Traffic monitoring and management systems.
  • Wildlife monitoring and conservation efforts.

Problems solved by this technology:

  • Efficient monitoring of large areas by automatically adjusting the imaging range based on detected objects.
  • Improved accuracy in object detection through machine learning.
  • Reduction in false alarms and unnecessary alerts by using a trained model.

Benefits of this technology:

  • Enhanced security and safety by effectively monitoring and detecting objects in real-time.
  • Reduction in human effort and resources required for surveillance.
  • Improved efficiency and accuracy in object detection.
  • Potential for continuous learning and improvement through the use of teacher images for machine learning.


Original Abstract Submitted

A control apparatus includes a processor that controls a surveillance camera. The processor enables switching between a first surveillance mode in which the surveillance camera is caused to perform imaging to acquire a first captured image and an imaging range is changed according to a given instruction, and a second surveillance mode in which the surveillance camera is caused to perform imaging to acquire a second captured image, a trained model that has been trained through machine learning is used to detect an object that appears in the second captured image, and the imaging range is changed according to a detection result, and outputs the first captured image acquired in the first surveillance mode as a teacher image for the machine learning.

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