A salient object detection method based on multi-level context information fusion

A technology of object detection and context, applied in the field of image processing, can solve the problem of not making full use of context information, and achieve the effect of accurate salient object detection

Active Publication Date: 2019-05-17
NANKAI UNIV
View PDF5 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the technical problem that the context information contained in the image cannot be fully utilized in the prior art, and to provide a salient object detection method based on multi-level context information fusion

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A salient object detection method based on multi-level context information fusion
  • A salient object detection method based on multi-level context information fusion
  • A salient object detection method based on multi-level context information fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0019] A salient object detection method based on multi-level context information fusion, the specific operation of this method is as follows:

[0020] a. This network model is an "encoding-decoding" convolutional neural network model with mirror connections, and the encoding part can be mentioned in the article "Very Deep Convolutional Networks for Large-Scale Image Recognition" published by Karen Simonyan The VGG16 architecture can also be the ResNet architecture mentioned in the article "Deep residual learning for image recognition" published by Kaiming He, or other basic network architectures. For the VGG16 network, such as figure 1 As shown, in the basic network architecture, we fi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a salient object detection method based on multi-level context information fusion. The object of the method is to construct and utilize multi-level context features to performimage saliency detection. According to the method, a new convolutional neural network architecture is designed, and the new convolutional neural network architecture is optimized in a manner of convolution from a high layer to a bottom layer, so that the context information on different scales is extracted for an image, and the context information is fused to obtain a high-quality image saliency map. The salient region detected by using the method can be used for assisting other visual tasks.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a salient object detection method based on multi-level context feature fusion. Background technique [0002] Salient object detection, also known as saliency detection, aims to simulate the human visual system to detect salient objects or regions in an image. Salient object detection techniques have broad applications in computer vision, such as image retrieval, visual tracking, scene classification, content-based video compression, and weakly supervised learning. Although many important saliency models have been proposed, the accuracy of saliency detection is still unsatisfactory, especially in many complex scenes. [0003] Traditional saliency detection methods usually manually design many underlying features and prior knowledge, but these features and prior knowledge are difficult to describe semantic objects and scenes. Recent advances in salient object...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/32G06N3/04G06N3/08
Inventor 程明明刘云
Owner NANKAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap