Interactive product image search with complex scenes
Xiao Ying Wu, Xian-Ping Deng, Ling-Ling Liang, Qiang Peng · 2012
Online shopping becomes a convenient way for billions for web users to purchase the products, especially clothes. A large portion of the product images are various types of apparel often including a human model from cluttered and non-uniform natural backgrounds, which makes visual product search a challenging task. In this work, we propose an approach for interactive product image search with complex scenes, which combines the interactive image segmentation for query images, and efficient graph-based principal object extraction for backend image database to extract the foreground objects, respectively. Experiments on a large scale dataset with 1.36 million product images crawled from Taobao demonstrate the effectiveness of the proposed solution.