Shopping image collaborative segmenting method

A collaborative segmentation and image technology, applied in the field of image processing and search engines, can solve problems such as difficulty in searching shopping images and complex scenes of shopping images, and achieve the effect of improving retrieval accuracy and eliminating interference
CN105809683AInactive Publication Date: 2016-07-27SOUTHWEST JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
SOUTHWEST JIAOTONG UNIV
Publication Date
2016-07-27
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a shopping image collaborative segmenting method for performing collaborative segmentation on a plurality of input shopping images containing one piece of garment automatically and extracting garment areas in the images. According to the invention, foreground (garment) areas and background areas in the shopping images are positioned by using an upper body detection algorithm and an image distinctive area detecting algorithm; a Gaussianmixed model is adopted for performing unified modeling on the foreground and the background of all the garment images and a collaborative segmentation objective function is established; then a minimum cut algorithm is used for performing iteration solving of the objective function; and finally the segmentation results of all the images are obtained. The method is suitable for being applied to e-commerce websites and online shopping websites. Interference on image retrieval caused by complex background can be eliminated and searching accuracy of searching engines can be improved.
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Description

technical field

[0001] The invention relates to image processing and search engine technology, in particular to a collaborative segmentation method for multiple images containing the same clothing on a shopping website. Background technique

[0002] Visual search of shopping images has been a research hotspot in academia and industry in recent years. However, problems such as shopping image background clutter, multi-object coexistence, and object occlusion make large-scale image search a challenging research topic.

[0003] E-commerce and online shopping sites, such as Taobao, Amazon, Tencent Paipai, etc., usually have a large number of shopping pictures containing people (such as models). After seeing or searching a large number of product images, customers can learn the details and various aspects of the product by clicking the link of the product they are interested in.

[0004] At the same time, in order to fully display the wearing effect of clothing, shopping website ...

Claims

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