Name
Abstract | ||
|---|---|---|
Multiple projectors with partially overlapping regions can be used to project a seamless image on a large projection surface. With the advent of high-resolution photography, such systems are gaining popularity. Experts set up such projection systems by subjectively identifying the types of errors induced by the system in the projected images and rectifying them by optimizing (correcting) the parameters associated with the system. This requires substantial time and effort, thus making it difficult to set up such systems. Moreover, comparing the performance of different multi-projector display (MPD) systems becomes difficult because of the subjective nature of evaluation. In this work, we present a framework to quantitatively determine the quality of an MPD system and any image projected using such a system. We have divided the quality assessment into geometric and photometric qualities. For geometric quality assessment, we use Feature Similarity Index (FSIM) and distance-based Scale Invariant Feature Transform (SIFT). For photometric quality assessment, we propose to use a measure incorporating Spectral Angle Mapper (SAM), Intensity Magnitude Ratio (IMR) and Perceptual Color Difference (Delta E). We have tested the proposed framework and demonstrated that it provides an acceptable method for both quantitative evaluation of MPD systems and estimation of the perceptual quality of any image projected by them. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3837/tiis.2015.06.015 | KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
Keywords | Field | DocType |
multi-projector display,geometric and photometric quality,quantitative quality assessment | Computer vision,Scale-invariant feature transform,Magnitude (mathematics),Computer science,Photography,Artificial intelligence,Color difference,Perception | Journal |
Volume | Issue | ISSN |
9 | 6 | 1976-7277 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Umer Kakli | 1 | 0 | 0.34 |
| Hassaan Saadat Qureshi | 2 | 0 | 0.34 |
| Muhammad Murtaza Khan | 3 | 134 | 14.34 |
| Rehan Hafiz | 4 | 28 | 7.93 |
| Yongju Cho | 5 | 23 | 6.00 |
| Unsang Park | 6 | 815 | 36.32 |