Interactive difficult portrait retrieval method, client and system

Abstract

The invention discloses an interactive difficult portrait retrieval method, client and system, and relates to the technical field of portrait recognition retrieval. The method comprises the followingsteps: acquiring an image, and converting the image into an image representation set based on semantic attribute tags; receiving a query input by a user, and obtaining semantic attribute information selected by the user for the query; marking significance semantic attributes according to the selection of a user, classifying the image representation set into a significance attribute image set and anon-significance attribute image set according to whether the image has the significance semantic attributes or not, and respectively classifying and sequencing the significance attribute image set and the non-significance attribute image set; generating an initial candidate sorting queue according to a sorting result; and obtaining a final target determined by the user through mixed similarity reordering interactive retrieval. The method is reasonable in manual workload, high in retrieval success rate, high in convergence rate, wide in application range and particularly suitable for difficult portrait retrieval application in the public security industry.

Description

technical field [0001] The present invention relates to the technical field of portrait recognition retrieval, in particular to a method, client and system for interactive difficult portrait retrieval. Background technique [0002] The method of portrait retrieval (also known as portrait image retrieval) mainly uses artificial recognition method and / or portrait recognition technology to retrieve the portraits in the picture data and obtain the retrieval results. The key to portrait retrieval technology lies in the content analysis and understanding of portrait pictures, that is, using machine vision to extract semantic information from portrait pictures for retrieval. The semantic information reflects the content of portraits and also constitutes the features on which portrait retrieval is based. The retrieval algorithm is based on The similarity of semantic features is used to sort the retrieval results. For portrait image retrieval, the semantic feature is required to des...

AI Technical Summary

Problems solved by technology

However, on the one hand, due to the difference in the "sensitive attributes" of human vision and machine vision, there is a large "semantic gap" between human eyes and machine vision, which has caused great troubles to image recognition work; on the other hand, the current interactive The traditional retrieval technology is usually an interactive retrieval method based on random candidate selection, which requires a large number of manual operations, and the number of cycles increases greatly in medium-to-large-scale or similar sample sets, and even falls into an unsolvable state.

Images