Results - Details
Search command : Author="Μουχτάρης"
And Author="Αθανάσιος"
Current Record: 8 of 29
|
Identifier |
000408512 |
Title |
Automatic organization of user generated content based on audio correlations |
Alternative Title |
Αυτόματη οργάνωση περιεχομένου προερχόμενου από πληθοπωρισμό βάσει συσχετίσεων στο ηχητικό υλικό |
Author
|
Χωνιανάκης, Σταύρος Π.
|
Thesis advisor
|
Μουχτάρης, Αθανάσιος
|
Reviewer
|
Τσακαλίδης, Παναγιώτης
Αργυρός, Αντώνιος
|
Abstract |
With the proliferation of smart-phones and portable electronic devices, more and more
of us become engaged in the process of capturing and sharing audiovisual content from
public events that we attend. Such User Generated Content (UGC) can be very valuable
to the broadcasters and producers associated to the professional coverage of such events,
as it may enrich the footage or provide coverage for parts of the event that have not been
captured by the professional equipment. Yet, it is not trivial to organize this content in
a way that it can be usable for the said purpose. For example, as user generated content
lacks metadata which is informative about the exact location and time of recording, it
would require enormous time and effort from the professional editor to manually search
for videos referring to a particular segment of the event, or to group and temporally align
multiple videos overlapping in space and time.
Fortunately, as several works have demonstrated in the past, it is possible to automatically
organize such content by exploiting the correlations in the audio streams available
in the UGC. Rather than working with the raw audio data, such correlations are much
more efficiently revealed based on fingerprints extracted from each user generated audio
recording. Audio fingerprinting finds use as the means for providing a compact and
concrete content based signature, by retaining the maximum acoustically relevant information,
showing significant robustness to variations with respect to the audio format, the
induced noise and distortion in each audio recording.
In this thesis, we use audio fingerprint cross-correlation as the means to detect and synchronize
temporally overlapping user generated audio recordings of the same event and
we evaluate our tools based on two datasets that we have acquired ourselves; a musical
concert and a football match. We perform an extensive comparison based on different
state of the art fingerprinting techniques and we propose a novel fingerprinting algorithm
with significantly better organization performance for the case of the athletic event. We
propose a generalizable scheme for fingerprint cross-correlation and we present an approach
inspired by graph theory for clustering recordings from the same temporal segment of the public event into the same group.
|
Language |
English |
Subject |
Audio clustering and matching |
|
Audio fingerprinting |
|
Audio sychronization |
|
Αποτυπώματα ήχου |
|
Ομαδοποίηση αρχείων ήχου |
|
Συγχρονισμός αρχείων ήχου |
Issue date |
2017-03-17 |
Collection
|
School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
|
|
Type of Work--Post-graduate theses
|
Permanent Link |
https://elocus.lib.uoc.gr//dlib/f/a/e/metadata-dlib-1488531833-92984-7064.tkl
|
Views |
712 |