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merofeev-ss_robust_metric-f35b79a (0, 2014-10-25)
merofeev-ss_robust_metric-f35b79a\LICENSE.txt (1542, 2014-10-25)
merofeev-ss_robust_metric-f35b79a\example.m (1621, 2014-10-25)
merofeev-ss_robust_metric-f35b79a\ss_robust_metric.m (4933, 2014-10-25)

Robust Saliency Map Comparison ========= ss_robust_metric MATLAB function performs comparison of saliency video sequence with ground-truth saliency video sequence using the method described in "Objective evaluation" section of > Y. Gitman, M. Erofeev, D. Vatolin, A. Bolshakov, A. Fedorov. "Semiautomatic Visual-Attention Modeling and > Its Application to Video Compression". 2014 IEEE International Conference on Image Processing (ICIP). > Paris, France, pp. 1105-1109. The comparison carried out by the function is almost invariant to all common transformation, thus it allows to carry out fare comparisons of saliency models. Features --------- - Metric is invariant to - Black and white level corrections - Gamma correction - Mixing method with Center Prior - Finds the best center prior model for ground-truth sequence Usage ----- ```MATLAB function [ ss,per_frame_ss ] = ss_robust_metric(src_avi, gt_avi,sampling_density,optimization_iterations) ``` Input arguments: - `src_avi` - path to AVI file with saliency sequence (uncompressed AVI recommended) - `gt_avi` - path to AVI file with ground-truth saliency sequence (uncompressed AVI recommended) - `sampling_density` - [DEFAULT VALUE = 400] sets frame sampling frequency for parameter optimization. Lower value leads to more precise results but increases computation time - `optimization_iterations` - [DEFAULT VALUE = 100] set how many times method will try to find global extrema. Higer value leads to more precise results but increases computation time Output arguments: - `ss - final` metric value. Higher metric values stand for higher correlation with ground-truth - `per_frame_ss` - vector of per-frame metric values > NOTE 1: First run of the the function with new ground-truth sequence takes longer than subsequent runs. On the first run method > selects centre prior model for the ground-truth video. The selected ground-truth model will be cached for future used in `*_cp.png` > file > > NOTE 2: The method works really slow (it is the cost of its robustness), please, be patient Usage example ------------ File `example.m` contains usage example. It performs comparison of two saliency sequences and visualizes its results. Misc ----- You can get ground-truth saliency sequencies from the [project website][]. With any questions regarding this code usage you can contact Mikhail Erofeev merofeev@graphics.cs.msu.ru If you use this code in your research please cite the following paper: > Y. Gitman, M. Erofeev, D. Vatolin, A. Bolshakov, A. Fedorov. "Semiautomatic Visual-Attention Modeling and > Its Application to Video Compression". 2014 IEEE International Conference on Image Processing (ICIP). > Paris, France, pp. 1105-1109. [project website]: http://compression.ru/video/savam/ "project website"

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