Enabling low bitrate mobile visual recognition - A performance versus bandwidth evaluation
Journal
2013 ACM Multimedia Conference
Pages
73-82
ISBN
9781450324045
Date Issued
2013
Author(s)
Abstract
The rapid development of technologies in both hardware and software have made content-based multimedia services feasi- ble on mobile devices such as smartphones and tablets; and the strong needs for mobile visual search and recognition have been emerging. While many real applications of vi- sual recognition require a large scale recognition systems, the same technologies that support server-based scalable visual recognition may not be feasible on mobile devices due to the resource constraints. Although the client-server framework ensures the scalability, the real-time response subjects to the limitation on network bandwidth. Therefore, the main challenge for mobile visual recognition system should be the recognition bitrate, which is the amount of data transmis- sion under the same recognition performance. For this work, we exploit and compare various strategies such as compact features, feature compression, feature signatures by hash- ing, image scaling, etc., to enable low bitrate mobile visual recognition. We argue that thumbnail image is a competi- Tive candidate for low bitrate visual recognition because it carries multiple features at once and multi-feature fusion is important as the size of semantic space increases. Our eval- uations on two subsets of ImageNet, both contain more than 10,000 images with 19 and 137 categories, verify the efficacy of thumbnail images. We further suggest a new strategy that combines single (local) feature signature and the thumbnail image, which achieves significant bitrate reduction from (av- erage) 102,570 to 4,661 bytes with merely (overall) 10% per- formance degradation. Copyright ? 2013 ACM.
Subjects
Bitrate; Mobile image recognition; Multi- modal fusion; Thumbnail image
SDGs
Other Subjects
Bit rates; Client-server framework; Content-based multimedia; Hardware and software; Mobile visual searches; Multi-feature fusion; Recognition systems; Thumbnail image; Image recognition; Mobile devices; Multimedia services; Semantics; Image coding
Type
conference paper