M
Michael G. Strintzis
Researcher at Aristotle University of Thessaloniki
Publications - 240
Citations - 6529
Michael G. Strintzis is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Motion estimation & Image segmentation. The author has an hindex of 44, co-authored 240 publications receiving 6319 citations. Previous affiliations of Michael G. Strintzis include Information Technology Institute & University of Pittsburgh.
Papers
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Journal ArticleDOI
Rate—distortion optimal fast thresholding for MPEG—2 image sequence coding
TL;DR: The proposed technique combines R—D optimal coefficient thresholding and some elements of the MPEG—2 rate control model and results in a new video encoding scheme, which offers in most cases a higher representation quality than “Test Model 5”.
Journal Article
A Novel Peer-to-peer Payment Protocol.
TL;DR: In this paper, the authors present a secure, anonymous and practical payment protocol for peer-to-peer commerce transactions, designed to enable every user to both buy and sell items.
Proceedings ArticleDOI
Motion and disparity estimation using rate-distortion theory for very low bit rate and multiview image sequence coding
TL;DR: A rate-distortion framework is used to define a displacement vector-field estimation technique for use in video coding that achieves maximum reconstructed image quality under the constraint of a target bitrate for the coding of the vector sequence.
Journal ArticleDOI
Optimal reconstruction from quantized data
TL;DR: This paper shows how a statistically non-optimal quantizer (e.g. a uniform quantizer) can be improved by a simple scaling operation before reconstructing the original value.
Book ChapterDOI
Multimedia Indexing, Search, and Retrieval in Large Databases of Social Networks
Theodoros Semertzidis,Dimitrios Rafailidis,Eleftherios Tiakas,Michael G. Strintzis,Petros Daras +4 more
TL;DR: In this chapter, an overview of multimedia indexing and searching algorithms, following the data growth curve, is presented in detail and pure multimedia content retrieval issues are presented.