Towards an All-Purpose Content-Based Multimedia Information Retrieval System
February 11, 2019 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ralph Gasser, Luca Rossetto, Heiko Schuldt
arXiv ID
1902.03878
Category
cs.MM: Multimedia
Cross-listed
cs.IR
Citations
16
Venue
arXiv.org
Last Checked
2 months ago
Abstract
The growth of multimedia collections - in terms of size, heterogeneity, and variety of media types - necessitates systems that are able to conjointly deal with several forms of media, especially when it comes to searching for particular objects. However, existing retrieval systems are organized in silos and treat different media types separately. As a consequence, retrieval across media types is either not supported at all or subject to major limitations. In this paper, we present vitrivr, a content-based multimedia information retrieval stack. As opposed to the keyword search approach implemented by most media management systems, vitrivr makes direct use of the object's content to facilitate different types of similarity search, such as Query-by-Example or Query-by-Sketch, for and, most importantly, across different media types - namely, images, audio, videos, and 3D models. Furthermore, we introduce a new web-based user interface that enables easy-to-use, multimodal retrieval from and browsing in mixed media collections. The effectiveness of vitrivr is shown on the basis of a user study that involves different query and media types. To the best of our knowledge, the full vitrivr stack is unique in that it is the first multimedia retrieval system that seamlessly integrates support for four different types of media. As such, it paves the way towards an all-purpose, content-based multimedia information retrieval system.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Multimedia
R.I.P.
๐ป
Ghosted
๐
๐
Old Age
Quality Assessment of In-the-Wild Videos
R.I.P.
๐ป
Ghosted
Viewport-Adaptive Navigable 360-Degree Video Delivery
R.I.P.
๐ป
Ghosted
A Comprehensive Survey on Cross-modal Retrieval
R.I.P.
๐ป
Ghosted
An Overview of Cross-media Retrieval: Concepts, Methodologies, Benchmarks and Challenges
R.I.P.
๐ป
Ghosted
A Convolutional Neural Network Approach for Post-Processing in HEVC Intra Coding
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted