Zobrazeno 1 - 10
of 18
pro vyhledávání: '"R. Gnana Praveen"'
Automatic estimation of pain intensity from facial expressions in videos has an immense potential in health care applications. However, domain adaptation (DA) is needed to alleviate the problem of domain shifts that typically occurs between video dat
Externí odkaz:
http://arxiv.org/abs/2010.15675
Multimodal analysis has recently drawn much interest in affective computing, since it can improve the overall accuracy of emotion recognition over isolated uni-modal approaches. The most effective techniques for multimodal emotion recognition efficie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83d53096ad095864903969047109a67c
In the recent years, there has been a shift in facial behavior analysis from the laboratory-controlled conditions to the challenging in-the-wild conditions due to the superior performance of deep learning based approaches for many real world applicat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94a8e214bf882ba84ef4b75eb374cc44
Publikováno v:
FG
Automatic pain assessment has an important potential diagnostic value for populations that are incapable of articulating their pain experiences. As one of the dominating nonverbal channels for eliciting pain expression events, facial expressions has
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16bab817b09ecbd5620d0254c822b8ed
https://doi.org/10.1109/fg47880.2020.00139
https://doi.org/10.1109/fg47880.2020.00139
Estimation of pain intensity from facial expressions captured in videos has an immense potential for health care applications. Given the challenges related to subjective variations of facial expressions, and operational capture conditions, the accura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f18ef73b9f8cdca823a85bcaa0a1a463
Automatic pain assessment has an important potential diagnostic value for populations that are incapable of articulating their pain experiences. As one of the dominating nonverbal channels for eliciting pain expression events, facial expressions has
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62c442807ea16aa46645a670b0914f13
Publikováno v:
Multimedia Tools and Applications. 74:9323-9338
This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf7992cc227b9b41e2b769210a63cb63
https://doi.org/10.1007/s11042-014-2083-2
https://doi.org/10.1007/s11042-014-2083-2
Akademický článek
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Publikováno v:
ICIP
In this paper, we have proposed a simple yet robust novel approach for segmentation of high density crowd flows based on super-pixels in H.264 compressed videos. The collective representation of the motion vectors of the compressed video sequence is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::318c5bc02033c17decf6ad596b0ee850
https://doi.org/10.1109/icip.2014.7025470
https://doi.org/10.1109/icip.2014.7025470
Autor:
R. Venkatesh Babu, R. Gnana Praveen
Publikováno v:
2014 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).
In this work, we have explored the prospect of segmenting crowd flow in H.264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H.264 compressed domain. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18cf08cbacc1c530779f325a090b9f81
https://doi.org/10.1109/conecct.2014.6740330
https://doi.org/10.1109/conecct.2014.6740330