A Method of Image Position Estimation Based on Region Mining and Spatial Coding

Abstract

The invention discloses an image position estimation method based on region mining and spatial coding, which is composed of an offline part and an online part. The offline part includes: extracting global features of images in a GPS image library, and clustering images; For each image in , region mining and BOW location descriptor generation are performed; finally, based on visual words, an inverted index table is built for the entire GPS image library. The online part includes: obtaining the candidate image set of the input image through global feature extraction and matching; performing the same operations on the input image as the region mining and BOW position descriptor generation steps in the offline part; using the inverted index table in the offline part to perform Region-based image matching to finally obtain the GPS location of the input image.

Description

Technical field [0001] The invention relates to a multimedia retrieval technology for social network data management, in particular to a retrieval method of social network picture materials. Background technique [0002] With the continuous popularization of social networks and the rapid development of multimedia technology, the scale of digital multimedia uploaded by users has grown at an explosive rate. Well-known picture sharing websites such as Flickr have uploaded 5 billion pictures in total. The number of pictures uploaded on social networks is even more alarming, with Facebook alone reaching 60 billion. In China, Renren.com and Kaixin.com have become the main social networking sites for uploading and sharing. Therefore, for large-scale multimedia data (picture data), how to quickly and effectively conduct information mining and image retrieval has become an urgent need for people, and content-based image retrieval has also emerged. With the improvement of living standar...

AI Technical Summary

Problems solved by technology

However, in the case of complex scenes, the generation of overall features will cover up the features we really want to retrieve, and the recognition results are often unsatisfactory.

[0004] Although the method of BOW and inverted index structure can improve the efficiency, because BOW will have errors in the quantization process, and the spatial position relationship between feature points is ignored, so people increase the spatial position relationship. Research

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