Euclidean Image Embedding in view of Similarity Ranking in Auction Search by Image
نویسندگان
چکیده
We propose an Euclidean embedding image representation, which serves to rank auction item images through wide range of semantic similarity spectrum, in the order of the relevance to the given query image much more effective than the baseline method in terms of a graded relevance measure. Our method uses three stream deep convolutional siamese networks to learn a distance metric and we leverage search query logs of an auction item search of the largest auction service in Japan. Unlike previous approaches, we define the inter-image relevance on the basis of user queries in the logs used to search each auction item, which enables us to acquire the image representation preserving the features concerning user intents in real e-commerce world.
منابع مشابه
Steganalysis of embedding in difference of image pixel pairs by neural network
In this paper a steganalysis method is proposed for pixel value differencing method. This steganographic method, which has been immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image is di_erent as compared with a cover image. A number of characteristics are identified in the di...
متن کاملUsing Text Surrounding Method to Enhance Retrieval of Online Images by Google Search Engine
Purpose: the current research aimed to compare the effectiveness of various tags and codes for retrieving images from the Google. Design/methodology: selected images with different characteristics in a registered domain were carefully studied. The exception was that special conceptual features have been apportioned for each group of images separately. In this regard, each group image surr...
متن کاملAccuracy improvement of Best Scanline Search Algorithms for Object to Image Transformation of Linear Pushbroom Imagery
Unlike the frame type images, back-projection of ground points onto the 2D image space is not a straightforward process for the linear pushbroom imagery. In this type of images, best scanline search problem complicates image processing using Collinearity equation from computational point of view in order to achieve reliable exterior orientation parameters. In recent years, new best scanline sea...
متن کاملA Comparing between the impacts of text based indexing and folksonomy on ranking of images search via Google search engine
Background and Aim: The purpose of this study was to compare the impact of text based indexing and folksonomy in image retrieval via Google search engine. Methods: This study used experimental method. The sample is 30 images extracted from the book “Gray anatomy”. The research was carried out in 4 stages; in the first stage, images were uploaded to an “Instagram” account so the images are tagge...
متن کاملEfficient Bootsrapping and Query Adaptive Ranking for Image Search
Scalable image search based on visual similarity has been an active topic of research in recent years. State-of-the-art solutions often use hashing methods to embed high-dimensional image features into Hamming space, where search can be performed in real-time based on Hamming distance of compact hash codes. Unlike traditional metrics (e.g., Euclidean) that offer continuous distances, the Hammin...
متن کامل