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Image processing method, image processing device, and computer-readable recording medium

An image processing and image technology, which is applied in image data processing, computer components, calculation, etc., to achieve the effect of suppressing quality deviation

Active Publication Date: 2020-09-11
PANASONIC INTELLECTUAL PROPERTY CORP OF AMERICA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In addition, in machine learning, it is known that accuracy improves when a large amount of data (big data) is provided as learning data.

Method used

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  • Image processing method, image processing device, and computer-readable recording medium
  • Image processing method, image processing device, and computer-readable recording medium
  • Image processing method, image processing device, and computer-readable recording medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment approach 1

[0090] [Structure of Image Processing Device 10 ]

[0091] figure 1 It is a diagram showing an example of the functional configuration of the image processing device 10 in the first embodiment.

[0092] The image processing device 10 performs image processing to mechanically label annotations that would require a high degree of recognition for a worker on the annotation data stored in the storage unit 20 , and outputs the annotation data to the storage unit 30 as learning data. In the present embodiment, the annotation data is a plurality of images captured by an on-vehicle camera, to which annotations indicating clearly existing moving objects have been added by crowdsourced staff. In addition, for annotating where a moving object clearly exists in an image, a worker is not required to perform a high degree of recognition, so individual differences among workers are less likely to occur, and there is no deviation in quality.

[0093] In this embodiment, if figure 1As shown...

Deformed example 1

[0154] In Embodiment 1, a person was cited as an example of a moving object, but the present invention is not limited thereto. Alternatively, the obstructing object may be a parked car and the moving object may be a door of the parked car. In this case, the size of the second area may be the same as that of the first area. Below, use Figure 14 and Figure 15 for a detailed description.

[0155] Figure 14 It is a diagram showing an example of a plurality of images acquired by the annotation unit 11 in Modification 1. FIG. 15 is a diagram showing an example of the second area determined by the annotation unit 11 in the first modification.

[0156] Annotation section 11 acquisition in Modification 1 Figure 14 As shown, a plurality of images including frame 103a, frame 103b, ..., at least a part of the frames of the plurality of images include a car parked, that is, an obstruction 1032 and a car in the vicinity of the obstruction 1032 as a driving The moving object 62 is a...

Deformed example 2

[0161] In Modification 1, as an example of a moving object, the door of a car was cited as an example, but it is not limited thereto. A moving object can also be an object used by children for play such as a ball or a flying saucer. In this case, the second area may be an area having the same size as the area obtained by enlarging the first area in the height direction in the image at the first time point. Below, use Figure 16 as well as Figure 17 An example in which the moving object is a ball will be specifically described.

[0162] Figure 16 It is a diagram showing an example of a plurality of images acquired by the annotation unit 11 in Modification 2. FIG. 17 is a diagram showing an example of the second area determined by the annotation unit 11 in the second modification.

[0163] Annotation section 11 acquisition in Modification 2 Figure 16 As shown, a plurality of images including frame 104a, frame 104b, ..., frame 104n, at least some of the frames of the plu...

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PUM

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Abstract

Provided are an image processing method, an image processing device, and a computer-readable recording medium capable of suppressing variations in quality of learning data. The image processing method includes: a judging step (S102), of a plurality of images that are consecutive in time series and at least some of the images have been given a first comment indicating the first region, while starting from the last time in time series, and based on the presence or absence of The first comment determines whether there is a first region in the image; the decision step (S103), determines the image at the first moment when it is judged that there is no first region, and determines a part of the region containing the occluder in the image at the first moment In the second area, the second area indicates that the moving object is occluded and before the moving object appears in the driving path from the occluder, the size of the second area and the time sequence of the next moment of the first moment, that is, the second moment corresponding to the size of the first area in the image; and the adding step (S104), adding the second annotation representing the second area to the image at the second moment.

Description

technical field [0001] The present invention relates to an image processing method, an image processing device, and a program. Background technique [0002] In recent years, general object recognition based on machine learning technology using neural networks has attracted attention due to its high performance. [0003] However, in general object recognition based on a neural network, in order to lead to high recognition performance, it is necessary to perform learning processing using a large number of images marked with annotations (correct answer information) such as the name and type of objects to be recognized. [0004] In addition, in machine learning, it is known that accuracy improves when a large amount of data (big data) is provided as learning data. [0005] As one of the methods of collecting big data, there is a method of outsourcing to a third party using crowd-sourcing or the like. Crowdsourcing is a method of entrusting simple tasks (tasks) to unspecified m...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N5/232H04N5/272
CPCH04N5/272H04N23/951H04N23/611G06T11/00G06V40/10G06V20/58G06V10/7753G06F18/2155G06T11/60G08G1/04G08G1/166H04N7/183
Inventor 小冢和纪谷川彻齐藤雅彦
Owner PANASONIC INTELLECTUAL PROPERTY CORP OF AMERICA