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