4 research outputs found
Efficient Multimedia Similarity Measurement Using Similar Elements
Online social networking techniques and large-scale multimedia systems are
developing rapidly, which not only has brought great convenience to our daily
life, but generated, collected, and stored large-scale multimedia data. This
trend has put forward higher requirements and greater challenges on massive
multimedia data retrieval. In this paper, we investigate the problem of image
similarity measurement which is used to lots of applications. At first we
propose the definition of similarity measurement of images and the related
notions. Based on it we present a novel basic method of similarity measurement
named SMIN. To improve the performance of calculation, we propose a novel
indexing structure called SMI Temp Index (SMII for short). Besides, we
establish an index of potential similar visual words off-line to solve to
problem that the index cannot be reused. Experimental evaluations on two real
image datasets demonstrate that our solution outperforms state-of-the-art
method.Comment: 17 pages. arXiv admin note: text overlap with arXiv:1808.0961
WAN: Watermarking Attack Network
Multi-bit watermarking (MW) has been developed to improve robustness against
signal processing operations and geometric distortions. To this end, benchmark
tools that test robustness by applying simulated attacks on watermarked images
are available. However, limitations in these general attacks exist since they
cannot exploit specific characteristics of the targeted MW. In addition, these
attacks are usually devised without consideration of visual quality, which
rarely occurs in the real world. To address these limitations, we propose a
watermarking attack network (WAN), a fully trainable watermarking benchmark
tool that utilizes the weak points of the target MW and induces an inversion of
the watermark bit, thereby considerably reducing the watermark extractability.
To hinder the extraction of hidden information while ensuring high visual
quality, we utilize a residual dense blocks-based architecture specialized in
local and global feature learning. A novel watermarking attack loss is
introduced to break the MW systems. We empirically demonstrate that the WAN can
successfully fool various block-based MW systems.Comment: Seung-Hun Nam and Wonhyuk Ahn contributed equally to this work.
Corresponding author: Seung-Hun Na
Efficient Region of Visual Interests Search for Geo-multimedia Data
With the proliferation of online social networking services and mobile smart
devices equipped with mobile communications module and position sensor module,
massive amount of multimedia data has been collected, stored and shared. This
trend has put forward higher request on massive multimedia data retrieval. In
this paper, we investigate a novel spatial query named region of visual
interests query (RoVIQ), which aims to search users containing geographical
information and visual words. Three baseline methods are presented to introduce
how to exploit existing techniques to address this problem. Then we propose the
definition of this query and related notions at the first time. To improve the
performance of query, we propose a novel spatial indexing structure called
quadtree based inverted visual index which is a combination of quadtree,
inverted index and visual words. Based on it, we design a efficient search
algorithm named region of visual interests search to support RoVIQ.
Experimental evaluations on real geo-image datasets demonstrate that our
solution outperforms state-of-the-art method.Comment: 22 page
Robust and discriminative zero-watermark scheme based on invariant feature and similarity-based retrieval for protecting large-scale DIBR 3D videos
Digital rights management (DRM) of depth-image-based rendering (DIBR) 3D
video is an emerging area of research. Existing schemes for DIBR 3D video cause
video distortions, are vulnerable to severe signal and geometric attacks,
cannot protect 2D frame and depth map independently or can hardly deal with
large-scale videos. To address these issues, a novel zero-watermark scheme
based on invariant feature and similarity-based retrieval for protecting DIBR
3D video (RZW-SR3D) is proposed in this study. In RZW-SR3D, invariant features
are extracted to generate master and ownership shares for providing
distortion-free, robust and discriminative copyright identification under
various attacks. Different from traditional zero-watermark schemes, features
and ownership shares are stored correlatively, and a similarity-based retrieval
phase is designed to provide effective solutions for large-scale videos. In
addition, flexible mechanisms based on attention-based fusion are designed to
protect 2D frame and depth map independently and simultaneously. Experimental
results demonstrate that RZW-SR3D have superior DRM performances than existing
schemes. First, RZW-SR3D can extracted the ownership shares relevant to a
particular 3D video precisely and reliably for effective copyright
identification of large-scale videos. Second, RZW-SR3D ensures lossless,
precise, reliable and flexible copyright identification for 2D frame and depth
map of 3D videos.Comment: 31 pages, 7 figure