User-driven saliency maps for evaluating Region-of-Interest detection
Himawan, Ivan, Song, Wei, & Tjondronegoro, Dian W. (2011) User-driven saliency maps for evaluating Region-of-Interest detection. In IEEE Workshop on Applications of Computer Vision (WACV2011), 5-6 January 2011, Sheraton Keauhou Bay Resort and Spa, Kona, Hawaii.
Detection of Region of Interest (ROI) in a video leads to more efficient utilization of bandwidth. This is because any ROIs in a given frame can be encoded in higher quality than the rest of that frame, with little or no degradation of quality from the perception of the viewers.
Consequently, it is not necessary to uniformly encode the whole video in high quality. One approach to determine ROIs is to use saliency detectors to locate salient regions.
This paper proposes a methodology for obtaining ground truth saliency maps to measure the effectiveness of ROI detection by considering the role of user experience during the labelling process of such maps. User perceptions can be captured and incorporated into the definition of salience in a particular video, taking advantage of human visual recall within a given context. Experiments with two state-of-the-art saliency detectors validate the effectiveness of this approach to validating visual saliency in video. This paper will provide the relevant datasets associated with the experiments.
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|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Deposited On:||24 Jul 2011 22:37|
|Last Modified:||10 Nov 2015 00:04|
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