Method and device for detecting target object in image

A target object and target detection technology, which is applied in image enhancement, image analysis, image generation, etc., can solve the problems of low detection accuracy, high cost, and high computational complexity, and achieve the effect of low detection accuracy and consistent detection accuracy

Active Publication Date: 2020-04-28
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
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  • Application Information

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Problems solved by technology

At present, the 3D target detection method in the road scene is mainly based on the binocular camera or radar to obtain 3D data. This method has high requirements for the accuracy of the dept

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  • Method and device for detecting target object in image
  • Method and device for detecting target object in image

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Embodiment Construction

[0036] The present disclosure will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0037] It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

[0038] figure 1 An exemplary system architecture 100 to which the method for detecting a target object in an image or the apparatus for detecting a target object in an image of the present disclosure can be applied is shown.

[0039] figure 1 An exemplary system archi...

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Abstract

The invention relates to the field of artificial intelligence. The embodiment of the invention provides a method and device for detecting a target object in an image. The method comprises the following steps: executing the following prediction operations by using a pre-trained neural network: detecting a target object in a two-dimensional image, and determining a two-dimensional bounding box of the target object; determining a relative position constraint relationship between the two-dimensional bounding box of the target object and a three-dimensional projection bounding box obtained by projecting the three-dimensional bounding box of the target object into the two-dimensional image; and determining a three-dimensional projection bounding box of the target object according to the two-dimensional bounding box of the target object and the relative position constraint relationship between the two-dimensional bounding box and the three-dimensional projection bounding box of the target object. According to the method, the accuracy of target object position detection is improved.

Description

technical field [0001] Embodiments of the present disclosure relate to the field of computer technology, specifically to the field of artificial intelligence technology, and in particular to a method and device for detecting a target object in an image. Background technique [0002] In road scenes, the location detection of traffic participants can provide effective help for smart transportation, automatic driving, smart city systems, etc. At present, the 3D target detection method in the road scene is mainly based on binocular cameras or radars to obtain 3D data. This method has high requirements for the accuracy of the depth estimation algorithm, high computational complexity, and high cost. In addition, the point cloud generated by the radar is relatively sparse in the distance, and the detection accuracy is low. Contents of the invention [0003] Embodiments of the present disclosure propose a method and apparatus for detecting a target object in an image, a training ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06V10/764
CPCG06V20/647G06V10/25G06T7/73G06T2207/20084G06T2207/30236G06N3/084G06V20/58G06V10/82G06V10/764G06N3/045G06T7/70G06N3/04G06N3/08G06T11/20G06T2207/20081G06T2210/12G06F18/24G06F18/214
Inventor 叶晓青谭啸张伟孙昊丁二锐
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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