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Content-aware Video Compression
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In a video there are certain regions in the image that viewers focus on more than others, which are called the salient regions or Regions­Of-Interest (ROI). This thesis aims to improve the perceived quality of videos by improving the quality of these ROis while degrading the quality of the other non-ROI regions of a frame to keep the same bitrate as would have been the case otherwise. This improvement is achieved by using saliency maps generated using an eye tracker or a deep neural network and providing this information to a modified video encoder. In this thesis the open source x264 encoder was chosen to make use of this information. The effects of ROI encoding are studied for high quality 720p videos by encoding them at low bitrates. The results indicate that ROI encoding can improve subjective video quality when carefully applied.

Abstract [sv]

I en video £inns <let vissa delar av bilden som tittarna fokuserar mer pa an andra, och dessa kallas Region of Interest". Malet med den har upp­satsen ar att hoja den av tittaren upplevda videokvaliteten genom att minska kompressionsgraden ( och darmed hoja kvaliteten) i de iogon­fallande delarna av bilden, samtid som man hojer kompressionsgra­den i ovriga delar sa att bitraten blir den samma som innan andring­en. Den har forbattringen gors genom att anvanda Saliency Mapsss­om visar de iogonfallande delarna for varje bildruta. Dessa Saliency Maps"har antingen detekterats med hjalp av en Eye Tracker eller sa har de raknats fram av ett Neuralt Natverk. Informationen anvands sedan i en modifierad version av den oppna codecen x264 enligt en egen­designad algoritm. Effekten av forandringen har studerats genom att koda hogkvalitativa kallfiler vid lag bitrate. Resultaten indikerar att denna metod kan forbattra den upplevda kvaliteten av en video om den appliceras med ratt styrka.

Place, publisher, year, edition, pages
2019. , p. 51
Series
TRITA-EECS-EX ; 2019:102
Keywords [en]
region-of-interest, saliency map, bitrate, H.264, video com­pression, quantization offset
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-254394OAI: oai:DiVA.org:kth-254394DiVA, id: diva2:1331719
External cooperation
Entecon
Examiners
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-27Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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