18277723. INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM simplified abstract (NEC Corporation)
Contents
- 1 INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING 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 Original Abstract Submitted
INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM
Organization Name
Inventor(s)
Yusuke Shinohara of Tokyo (JP)
INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18277723 titled 'INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM
Simplified Explanation
The patent application describes an information processing apparatus that can estimate important and non-important regions in an image, replace regions with alternative data based on their importance levels, evaluate the replaced data, and train the system based on the evaluation value.
- The apparatus obtains input data containing image or point cloud data.
- It estimates levels of importance for multiple regions in a frame indicated by the input data.
- It replaces regions in the input data with alternative data according to their importance levels.
- It evaluates the replaced data to derive an evaluation value.
- It trains the system by referencing the evaluation value.
Potential Applications
This technology could be applied in image processing, object recognition, and computer vision systems.
Problems Solved
This technology helps in accurately identifying important regions in images, which can be crucial for various applications such as object detection and image analysis.
Benefits
The benefits of this technology include improved accuracy in identifying important regions in images, enhanced object recognition capabilities, and better overall performance in image processing tasks.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of advanced surveillance systems with improved object detection capabilities.
Possible Prior Art
One possible prior art for this technology could be existing image processing algorithms that focus on object recognition and region importance estimation.
What are the specific techniques used for estimating the levels of importance in different regions of the image?
The specific techniques used for estimating the levels of importance in different regions of the image are not detailed in the abstract. Further information on the algorithms or methods employed for this estimation would provide a clearer understanding of the technology.
How does the training process work for the estimating means with reference to the evaluation value?
The abstract mentions a training means for training the estimating means with reference to the evaluation value, but it does not elaborate on the specific training process. More information on the training methodology and how it improves the estimation of region importance would be beneficial for a comprehensive understanding of the technology.
Original Abstract Submitted
To provide a technique which makes it possible to suitably estimate an important region and a non-important region in an image, an information processing apparatus includes: an obtaining means for obtaining input data which includes at least one of image data and point cloud data; an estimating means for estimating levels of importance with respect to a respective plurality of regions which are included in a frame indicated by the input data; a replacing means for generating replaced data by replacing at least one of the plurality of regions, which are included in the input data, with alternative data in accordance with the levels of importance; an evaluating means for deriving an evaluation value by referring to the replaced data; and a training means for training the estimating means with reference to the evaluation value.
