Authors:
Bahar Pourazar
and
Oscar Meruvia-Pastor
Affiliation:
Memorial University of Newfoundland, Canada
Keyword(s):
Augmented Reality, Human Visual System, Binocular Stereo, Stereoacuity, Disparity, Stereo Correspondence.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Mobile Imaging
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
Abstract:
This paper suggests a comprehensive approach for the evaluation of stereo correspondence techniques based on the specific requirements of outdoor augmented reality systems. To this end, we present an evaluation model that integrates existing metrics of stereo correspondence algorithms with additional metrics that consider human factors that are relevant in the context of outdoor augmented reality systems. Our model provides modified metrics of stereoacuity, average outliers, disparity error, and processing time. These metrics have been modified to provide more relevant information with respect to the target application. We evaluate our model using two stereo correspondence methods: the OpenCV implementation of the semi-global block matching, also known as SGBM, which is a modified version of the semi-global matching by Hirschmuller; and our implementation of the solution by Mei et al., known as ADCensus. To test these methods, we use a sample of fifty-two image pairs selected from th
e Kitti stereo dataset, which depicts many situations typical of outdoor scenery. Experimental results show that our proposed model can provide a more detailed evaluation of both algorithms. Further, we discuss areas of improvement and suggest directions for future research.
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