Honda motor co., ltd. (20240104936). OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM simplified abstract
Contents
- 1 OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM
Organization Name
Inventor(s)
Masamitsu Tsuchiya of Wako-shi (JP)
OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104936 titled 'OBJECT DETECTION DEVICE, OBJECT DETECTION METHOD, AND STORAGE MEDIUM
Simplified Explanation
The object detection device described in the abstract utilizes a captured image of a surface to extract points of interest by analyzing differences in feature amounts between partial areas. Here are some key points to note:
- The device acquires a captured image of a surface with an inclination, then generates a low-resolution image by lowering the image quality.
- It defines multiple partial area sets within the low-resolution image, each containing partial areas in a target area.
- The total value is derived by comparing feature amounts between partial areas in each set and nearby partial areas to extract points of interest.
- The target area is obtained by cutting out a portion of the low-resolution image limited in a vertical direction to avoid overlap with other partial area sets.
Potential Applications
This technology can be applied in various fields such as:
- Autonomous driving systems for detecting obstacles and points of interest on roads.
- Surveillance systems for monitoring and tracking moving objects in real-time.
- Robotics for navigation and object recognition in dynamic environments.
Problems Solved
This technology addresses the following issues:
- Efficient object detection and tracking in complex environments.
- Improved accuracy in identifying points of interest on surfaces with inclinations.
- Enhanced image processing capabilities for low-resolution images.
Benefits
The benefits of this technology include:
- Increased efficiency in object detection and tracking tasks.
- Enhanced accuracy in identifying critical points of interest.
- Improved performance in analyzing images with varying qualities.
Potential Commercial Applications
Potential commercial applications of this technology include:
- Automotive industry for autonomous driving systems.
- Security and surveillance companies for advanced monitoring solutions.
- Robotics companies for developing intelligent navigation systems.
Possible Prior Art
One possible prior art for this technology could be the use of image processing algorithms in object detection systems. Another could be the application of feature extraction techniques in computer vision technologies.
Unanswered Questions
How does this technology handle varying lighting conditions in object detection?
The abstract does not mention how the device adjusts for different lighting conditions that may affect image quality and feature extraction.
What is the processing speed of this object detection device?
The abstract does not provide information on the processing speed of the device when executing the described image analysis tasks.
Original Abstract Submitted
an object detection device includes a storage medium configured to store computer-readable instructions, and a processor connected to the storage medium, in which the processor executes the computer-readable instructions to execute acquiring a captured image of a surface along which a mobile object is able to travel, which is captured with an inclination with respect to the surface, generating a low-resolution image obtained by lowering image quality of the captured image, defining a plurality of partial area sets each having partial areas in the low-resolution image, and deriving a total value obtained by totalizing differences in feature amount between the partial areas included in each of the plurality of partial area sets and partial areas in the vicinity to extract a point of interest on the basis of the total value, each of the plurality of partial area sets is defined to include a plurality of partial areas in a target area of each partial area set, and the target area is obtained by cutting out a part of the low-resolution image limited in a vertical direction so that at least a part thereof does not overlap with another partial area set in the vertical direction.
