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Texture features for object salience

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Figure 2: Our texture model. A local power spectrum is a 2D matrix with the dimensions representing orientation (horizontal axis) and frequencyACCEPTED MANUSCRIPT(vertical)
Figure 4: Visual comparison of results on the new texture salience dataset. The input images are shown on the left, the ground truth annotations![19], of the standard VOCUS2 method based on colour [14], and our new texture features used together with VOCUS
Figure 5 shows the results on the MSRA-1000 datasetACCEPTED MANUSCRIPTby Achanta et al
Figure 6: Evaluation on the PASCAL-S (left) and ECSSD (right) datasets. The deep learning method does best, but it can be clearly seen thatACCEPTED MANUSCRIPTthe use of texture features improves the performance of the VOCUS2 algorithm

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