Analysis of Disparity Maps for Detecting Saliency in Stereoscopic Video

Kopf, Stephan ; Guthier, Benjamin ; Schaber, Philipp ; Dittrich, Torben ; Effelsberg, Wolfgang

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URN: urn:nbn:de:bsz:180-madoc-330935
Document Type: Working paper
Year of publication: 2013
The title of a journal, publication series: Technical Reports
Volume: 13-003
Place of publication: Mannheim
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik IV (Effelsberg -2017)
MADOC publication series: Veröffentlichungen der Fakultät für Mathematik und Informatik > Institut für Informatik > Technical Reports
Subject: 004 Computer science, internet
Keywords (English): Video saliency , depth saliency , disparity maps , visual attention , stereoscopic video
Abstract: We present a system for automatically detecting salient image regions in stereoscopic videos. This report extends our previous system and provides additional details about its implementation. Our proposed algorithm considers information based on three dimensions: salient colors in individual frames, salient information derived from camera and object motion, and depth saliency. These three components are dynamically combined into one final saliency map based on the reliability of the individual saliency detectors. Such a combination allows using more efficient algorithms even if the quality of one detector degrades. For example, we use a computationally efficient stereo correspondence algorithm that might cause noisy disparity maps for certain scenarios. In this case, however, a more reliable saliency detection algorithm such as the image saliency is preferred. To evaluate the quality of the saliency detection, we created modified versions of stereoscopic videos with the non-salient regions blurred. Having users rate the quality of these videos, the results show that most users do not detect the blurred regions and that the automatic saliency detection is very reliable.

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