A novel superpixel-based saliency detection model for 360-degree images

@article{Fang2018ANS,
  title={A novel superpixel-based saliency detection model for 360-degree images},
  author={Yuming Fang and Xiaoqiang Zhang and Nevrez Imamoglu},
  journal={Signal Process. Image Commun.},
  year={2018},
  volume={69},
  pages={1-7}
}

A Content-Based Approach for Saliency Estimation in 360 Images

Experimental results show effectiveness of the proposed system with respect to ground truth saliency maps.

Geometric feature based approach for 360° image saliency estimation

A 360° image saliency estimation technique that combines standard low-level features along with multiple geometry-based features that reflects the geometry of an image to outperforms existing saliency models.

Recent Advances in Saliency Estimation for Omnidirectional Images, Image Groups, and Video Sequences

The emerging directions for research in the specialized literature are synthesized, which include novel representations for omnidirectional images, inter- and intra- image saliency decomposition for co-saliency, and saliency shift for video saliency estimation.

A Feature Integrated Saliency Estimation Model for Omnidirectional Immersive Images

ASaliency estimation model that considers the spherical properties of the images and outperforms existing saliency estimation models for 360° saliency map estimation.

Face-aware Saliency Estimation Model for 360° Images

In this paper, a saliency estimation technique for omni-directional images is presented, in which low-level features are combined with the detection of human faces to refine theSaliency estimation based on the low- level features by assigning a larger weight to the regions containing faces.

Unsupervised Change Detection from Remotely Sensed Images Based on Multi-Scale Visual Saliency Coarse-to-Fine Fusion

The results suggest that it is not entirely true that finer scale brings better CD result, and fusing multi-scale superpixel based saliency at a pixel level obtained a higher F1 score in the three experiments.

References

SHOWING 1-10 OF 36 REFERENCES

A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression

Extensive tests of videos, natural images, and psychological patterns show that the proposed PQFT model is more effective in saliency detection and can predict eye fixations better than other state-of-the-art models in previous literature.

Saliency Detection in the Compressed Domain for Adaptive Image Retargeting

The proposed image retargeting algorithm effectively preserves the visually important regions for images, efficiently removes the less crucial regions, and therefore significantly outperforms the relevant state-of-the-art algorithms, as demonstrated with the in-depth analysis in the extensive experiments.

Saliency Tree: A Novel Saliency Detection Framework

Extensive experimental results on five datasets with pixel-wise ground truths demonstrate that the proposed saliency tree model consistently outperforms the state-of-the-art saliency models.

Visual saliency estimation by nonlinearly integrating features using region covariances.

This work proposes to use covariance matrices of simple image features (known as region covariance descriptors in the computer vision community) as meta-features for saliency estimation and demonstrates that the proposed approach outperforms the state-of-art models on various tasks including prediction of human eye fixations, salient object detection, and image-retargeting.

Hierarchical Image Saliency Detection on Extended CSSD

This work proposes a multi-layer approach and constructs an extended Complex Scene Saliency Dataset (ECSSD) to include complex but general natural images and improves detection quality on many images that cannot be handled well traditionally.

Visual saliency detection: From space to frequency

A Universal Framework for Salient Object Detection

A novel universal framework for salient object detection, which aims to enhance the performance of any existing saliency detection method with distance weighting, adaptive binarization, and morphological closing is proposed.