Classification and Retrieval of Commodity Images Oriented to Internet Marketing

Abstract

Commodity display images oriented to Internet marketing play an important role in the supply and demand interaction and two-way communication between marketing personnel and consumers. Traditional commodity image classification is mainly conducted manually by the staff of online shopping platforms or the store maintenance staff, which is heavy in workload, high in cost and low in efficiency. To this end, this article studies classification and retrieval of commodity images oriented to Internet marketing. In this study, coarse-grained emotion is taken as priori information, and an image emotion classification network based on joint polarity detection is constructed. This article discusses the association rules between the color and texture of commodity images, the shape, styling features and contained emotion of concrete commodities. Besides, this article puts forwards an emotion-based retrieval method of commodity images oriented to Internet marketing, and presents a concrete train of thought of this method. The experimental result verifies the effectiveness of the classification and retrieval method of commodity images.