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A material retrieval method for cross-modal objects based on tactile texture features

A texture feature and cross-modal technology, applied in digital data information retrieval, electronic digital data processing, character and pattern recognition, etc., can solve problems such as cross-modal image retrieval methods that do not yet exist

Active Publication Date: 2020-04-03
TSINGHUA UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

However, no cross-modal image retrieval method based on tactile features exists yet.

Method used

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  • A material retrieval method for cross-modal objects based on tactile texture features
  • A material retrieval method for cross-modal objects based on tactile texture features
  • A material retrieval method for cross-modal objects based on tactile texture features

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Embodiment Construction

[0039] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and do not limit the protection scope of the present invention.

[0040] In order to better understand the present invention, an application example of a cross-modal object material retrieval method based on tactile texture features of the present invention is described in detail below.

[0041] The workflow of a cross-modal object material retrieval method based on tactile texture features proposed by the present invention includes the following steps:

[0042] 1) Selection of tactile texture training sample materials: According to the tactile properties, the training sample materials are divided into categories A with wood, meta...

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Abstract

The invention discloses a texture image cross-modal retrieval method based on tactile texture features, which belongs to the technical field of robot tactile recognition. The method of the present invention sequentially includes material selection of tactile texture training samples, establishment of tactile texture training data sets and texture image training data sets, feature extraction of tactile acceleration and texture image feature extraction, and correlation analysis of the two extracted feature vector sets Afterwards, the extraction of the corresponding retrieval features, the creation of the texture image retrieval database and the retrieval of the object material are carried out. The present invention uses the friction vibration signal of the textured surface as the tactile feature of the textured surface to retrieve the textured surface image most similar to the retrieved surface from the texture image retrieval database, that is, realizes the cross-modal object material retrieval based on the tactile feature. The present invention has higher accuracy rate, and makes up for the singleness of text description material.

Description

technical field [0001] The invention belongs to the technical field of robot tactile recognition, and in particular relates to a cross-modal object material retrieval method based on tactile texture features. Background technique [0002] With the development of intelligent manufacturing and global industrialization, object material recognition is widely used in many industrial fields such as e-commerce, leather textiles, and intelligent robots. The current material recognition is usually based on the texture image of the surface of the object to identify the material (such as wood, glass, plastic, steel and fiber, etc.) of the object in the image. However, texture image-based material recognition is easily affected by the shooting environment, and large intra-class apparent differences and small inter-class apparent differences usually lead to weakened distinguishability and robustness of texture features. In addition, texture images do not accurately reflect object proper...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/583G06K9/62
CPCG06F18/214
Inventor 刘华平郑文栋王博文孙富春
Owner TSINGHUA UNIV
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