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Fig. 18 | EURASIP Journal on Image and Video Processing

Fig. 18

From: Robust surface normal estimation via greedy sparse regression

Fig. 18

Robustness of sparse recovery methods against light calibration error. Top row: leftmost plot shows actual light positions used for generating the dataset. Remaining plots show miscalibrated light positions with angular perturbations (2°–32°, from left to right) from the actual light positions at random directions. Middle figure: boxplot of the angular error of normal maps under various degrees of light calibration error. Upper and lower border of blue boxes represent third (Q3) and first (Q1) quartiles, respectively. Upper and lower whiskers show 1.0 IQR extended from Q3 and Q1, respectively. Red bars in blue boxes represent medians. At each angular perturbation level, four sparse recovery methods are compared, symbolized by different markers on the median bar: IRL1 (cross), SBL (triangle) and OMP (diamond). Bottom figure: the medians of angular error

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