Saliency Detection in Video Advertisements using Gaze Analysis | Estimating the Salient Features in a Video through Gaze Detection Algorithm

Inam Ullah Khan (u. a.)

ISBN 10: 3659866261 / ISBN 13: 9783659866265

Published by LAP LAMBERT Academic Publishing, 2016

About this Item

Saliency Detection in Video Advertisements using Gaze Analysis | Estimating the Salient Features in a Video through Gaze Detection Algorithm | Inam Ullah Khan (u. a.) | Taschenbuch | 52 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659866265 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 103781465

Bibliographic Details

• Title: Saliency Detection in Video Advertisements using Gaze Analysis | Estimating the Salient Features in a Video through Gaze Detection Algorithm
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 3659866261
• ISBN 13: 9783659866265
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 96 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Detection of salient features in a video has a wide range of applications. Through gaze tracking, important and interesting features of a video can be highlighted. This data can be used to make the advertisements better and effective. Gaze detection gives an estimation of the points that were under more focus by the viewers. Greater the sample space of the data, better the generic estimation of important points. This data is further parsed through different algorithms to achieve a better accuracy. These algorithms also test the validity of the data or whether the data points collected are sufficient are not. Each algorithm used manipulates the data in a different way to get maximum coverage of all the possible aspects. Finally, the result obtained is a small region of the frame that captures the maximum attention of the viewer

About the Author

All authors are Electrical Engineering graduates from SEECS, NUST, Islamabad. Mr Inam is a consultant in the information technology industry. Mr Solaija is a research scientist with concentration in digital signal processing. Mr Faraz is a software developer at a cloud computing product company in the Silicon Valley