Joint compressive video coding and analysis with hidden markov model based weighted reconstruction [Sakli markof model tabanli agirlikli geriçatilma ile ortak sikiştirmali video kodlama ve analizi]

Küçük Resim Yok

Tarih

2013

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Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

This paper examines the performance of Hidden Markov Tree model based weights in reconstruction quality for an existing task-Aware compressive video coding system which aims object detection specifically. The existing system utilizes weights in reconstruction which are computed by tracking of the foreground object. The proposed system acquires similar average PSNR with the existing one which reported some improvement compared to the conventional unweighted reconstruction at low sampling rates. Furthermore, it is a little bit better than the existing system at higher sampling rates. It can be inferred from this study that Bayesian approaches that take account structural dependencies between transformation coefficients has the potential of improving reconstruction quality for such a compressive video coding system with object detection task. © 2013 IEEE.

Açıklama

2013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 24 April 2013 through 26 April 2013 -- Haspolat -- 98109

Anahtar Kelimeler

Compressed video coding, Compressive sensing, Hidden markov tree model, Object detection, Surveillance video, Weighted reconstruction

Kaynak

2013 21st Signal Processing and Communications Applications Conference, SIU 2013

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N/A

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