Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Eftychia Fotiadou"'
Autor:
Athanasios Papaioannou, Baris Gecer, Shiyang Cheng, Grigorios Chrysos, Jiankang Deng, Eftychia Fotiadou, Christos Kampouris, Dimitrios Kollias, Stylianos Moschoglou, Kritaphat Songsri-In, Stylianos Ploumpis, George Trigeorgis, Panagiotis Tzirakis, Evangelos Ververas, Yuxiang Zhou, Allan Ponniah, Anastasios Roussos, Stefanos Zafeiriou
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200731
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7262dc4e508460472ee6cad9736435ad
https://doi.org/10.1007/978-3-031-20074-8_27
https://doi.org/10.1007/978-3-031-20074-8_27
Publikováno v:
ACM Computing Surveys. 47:1-35
The expansion of the Internet over the last decade and the proliferation of online social communities, such as Facebook, Google+, and Twitter, as well as multimedia sharing sites, such as YouTube, Flickr, and Picasa, has led to a vast increase of ava
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1a913ce39dec2d5ad173a6cf650d099
https://doi.org/10.1145/2700381
https://doi.org/10.1145/2700381
Publikováno v:
FG
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
12th IEEE International Conference on Automatic Face and Gesture Recognition (FG)
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
12th IEEE International Conference on Automatic Face and Gesture Recognition (FG)
Unsupervised learning of invariant representations that efficiently describe high-dimensional time series has several applications in dynamic visual data analysis. Clearly, the problem becomes more challenging when dealing with multiple time series a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::162422c3cc0fb6d77a20cda53b51177f
https://doi.org/10.1109/fg.2017.66
https://doi.org/10.1109/fg.2017.66
Autor:
Nikos Nikolaidis, Eftychia Fotiadou
Publikováno v:
Pattern Recognition Letters. 49:48-54
We present two algorithms for person recognition from motion capture data.The first algorithm is based on a similarity measure between two sequences.The second algorithm combines dimensionality reduction and a Bag of Words approach.Correct person rec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a29adcdedc9655a1f8c18d6c71939f4
https://doi.org/10.1016/j.patrec.2014.06.005
https://doi.org/10.1016/j.patrec.2014.06.005
Publikováno v:
EUSIPCO
In this paper, we deal with the classification of Greek folk songs into 8 classes associated with the region of origin of the songs. Motivated by the way the sound is perceived by the human auditory system, auditory cortical representations are extra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7caa9d88046458a8310ab1e8e78f13b5
https://doi.org/10.1109/eusipco.2016.7760425
https://doi.org/10.1109/eusipco.2016.7760425
Publikováno v:
EUSIPCO
Dance traditions constitute a significant aspect of cultural heritage around the world. The organization, semantic analysis, and retrieval of dance-related multimedia content (i.e., music, video) in databases is, therefore, crucial to their preservat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de87339c69eb2bdb70f9e31194ef730e
https://doi.org/10.1109/eusipco.2016.7760221
https://doi.org/10.1109/eusipco.2016.7760221
Publikováno v:
SETN
In this paper we explore the problem of distinguishing Greek folk dances from other kinds of activities, as well as from other dance genres, using video recordings. For this purpose, we adopt dense trajectories descriptors along with a Bag of Words (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f89dd00084c04b8733e0aba4ac83fa9
https://doi.org/10.1145/2903220.2903221
https://doi.org/10.1145/2903220.2903221
Autor:
Nikos Nikolaidis, Eftychia Fotiadou
Publikováno v:
ICIP
In this paper we present an algorithm for efficient activity recognition operating upon human skeleton motion sequences, derived through motion capture systems or by analyzing the output of RGB-D sensors. Our approach is driven from the assumption th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f65353d8245daf40998e09d17e011c8
https://doi.org/10.1109/icip.2014.7025300
https://doi.org/10.1109/icip.2014.7025300