22,315 research outputs found
Video Fragmentation and Reverse Search on the Web
This chapter is focused on methods and tools for video fragmentation and reverse search on the web. These technologies can assist journalists when they are dealing with fake news—which nowadays are being rapidly spread via social media platforms—that rely on the reuse of a previously posted video from a past event with the intention to mislead the viewers about a contemporary event. The fragmentation of a video into visually and temporally coherent parts and the extraction of a representative keyframe for each defined fragment enables the provision of a complete and concise keyframe-based summary of the video. Contrary to straightforward approaches that sample video frames with a constant step, the generated summary through video fragmentation and keyframe extraction is considerably more effective for discovering the video content and performing a fragment-level search for the video on the web. This chapter starts by explaining the nature and characteristics of this type of reuse-based fake news in its introductory part, and continues with an overview of existing approaches for temporal fragmentation of single-shot videos into sub-shots (the most appropriate level of temporal granularity when dealing with user-generated videos) and tools for performing reverse search of a video on the web. Subsequently, it describes two state-of-the-art methods for video sub-shot fragmentation—one relying on the assessment of the visual coherence over sequences of frames, and another one that is based on the identification of camera activity during the video recording—and presents the InVID web application that enables the fine-grained (at the fragment-level) reverse search for near-duplicates of a given video on the web. In the sequel, the chapter reports the findings of a series of experimental evaluations regarding the efficiency of the above-mentioned technologies, which indicate their competence to generate a concise and complete keyframe-based summary of the video content, and the use of this fragment-level representation for fine-grained reverse video search on the web. Finally, it draws conclusions about the effectiveness of the presented technologies and outlines our future plans for further advancing them
CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference
The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the
world
Translating Video Recordings of Mobile App Usages into Replayable Scenarios
Screen recordings of mobile applications are easy to obtain and capture a
wealth of information pertinent to software developers (e.g., bugs or feature
requests), making them a popular mechanism for crowdsourced app feedback. Thus,
these videos are becoming a common artifact that developers must manage. In
light of unique mobile development constraints, including swift release cycles
and rapidly evolving platforms, automated techniques for analyzing all types of
rich software artifacts provide benefit to mobile developers. Unfortunately,
automatically analyzing screen recordings presents serious challenges, due to
their graphical nature, compared to other types of (textual) artifacts. To
address these challenges, this paper introduces V2S, a lightweight, automated
approach for translating video recordings of Android app usages into replayable
scenarios. V2S is based primarily on computer vision techniques and adapts
recent solutions for object detection and image classification to detect and
classify user actions captured in a video, and convert these into a replayable
test scenario. We performed an extensive evaluation of V2S involving 175 videos
depicting 3,534 GUI-based actions collected from users exercising features and
reproducing bugs from over 80 popular Android apps. Our results illustrate that
V2S can accurately replay scenarios from screen recordings, and is capable of
reproducing 89% of our collected videos with minimal overhead. A case
study with three industrial partners illustrates the potential usefulness of
V2S from the viewpoint of developers.Comment: In proceedings of the 42nd International Conference on Software
Engineering (ICSE'20), 13 page
I Know Why You Went to the Clinic: Risks and Realization of HTTPS Traffic Analysis
Revelations of large scale electronic surveillance and data mining by
governments and corporations have fueled increased adoption of HTTPS. We
present a traffic analysis attack against over 6000 webpages spanning the HTTPS
deployments of 10 widely used, industry-leading websites in areas such as
healthcare, finance, legal services and streaming video. Our attack identifies
individual pages in the same website with 89% accuracy, exposing personal
details including medical conditions, financial and legal affairs and sexual
orientation. We examine evaluation methodology and reveal accuracy variations
as large as 18% caused by assumptions affecting caching and cookies. We present
a novel defense reducing attack accuracy to 27% with a 9% traffic increase, and
demonstrate significantly increased effectiveness of prior defenses in our
evaluation context, inclusive of enabled caching, user-specific cookies and
pages within the same website
Survey of End-to-End Mobile Network Measurement Testbeds, Tools, and Services
Mobile (cellular) networks enable innovation, but can also stifle it and lead
to user frustration when network performance falls below expectations. As
mobile networks become the predominant method of Internet access, developer,
research, network operator, and regulatory communities have taken an increased
interest in measuring end-to-end mobile network performance to, among other
goals, minimize negative impact on application responsiveness. In this survey
we examine current approaches to end-to-end mobile network performance
measurement, diagnosis, and application prototyping. We compare available tools
and their shortcomings with respect to the needs of researchers, developers,
regulators, and the public. We intend for this survey to provide a
comprehensive view of currently active efforts and some auspicious directions
for future work in mobile network measurement and mobile application
performance evaluation.Comment: Submitted to IEEE Communications Surveys and Tutorials. arXiv does
not format the URL references correctly. For a correctly formatted version of
this paper go to
http://www.cs.montana.edu/mwittie/publications/Goel14Survey.pd
Automated Test Input Generation for Android: Are We There Yet?
Mobile applications, often simply called "apps", are increasingly widespread,
and we use them daily to perform a number of activities. Like all software,
apps must be adequately tested to gain confidence that they behave correctly.
Therefore, in recent years, researchers and practitioners alike have begun to
investigate ways to automate apps testing. In particular, because of Android's
open source nature and its large share of the market, a great deal of research
has been performed on input generation techniques for apps that run on the
Android operating systems. At this point in time, there are in fact a number of
such techniques in the literature, which differ in the way they generate
inputs, the strategy they use to explore the behavior of the app under test,
and the specific heuristics they use. To better understand the strengths and
weaknesses of these existing approaches, and get general insight on ways they
could be made more effective, in this paper we perform a thorough comparison of
the main existing test input generation tools for Android. In our comparison,
we evaluate the effectiveness of these tools, and their corresponding
techniques, according to four metrics: code coverage, ability to detect faults,
ability to work on multiple platforms, and ease of use. Our results provide a
clear picture of the state of the art in input generation for Android apps and
identify future research directions that, if suitably investigated, could lead
to more effective and efficient testing tools for Android
Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development
Mobile devices and platforms have become an established target for modern
software developers due to performant hardware and a large and growing user
base numbering in the billions. Despite their popularity, the software
development process for mobile apps comes with a set of unique, domain-specific
challenges rooted in program comprehension. Many of these challenges stem from
developer difficulties in reasoning about different representations of a
program, a phenomenon we define as a "language dichotomy". In this paper, we
reflect upon the various language dichotomies that contribute to open problems
in program comprehension and development for mobile apps. Furthermore, to help
guide the research community towards effective solutions for these problems, we
provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference
on Program Comprehension (ICPC'18
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