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Superpixel segmentation: A benchmark

Signal Processing: Image Communication, 2017
Abstract Various superpixel approaches have been published recently. These algorithms are assessed using different evaluation metrics and datasets resulting in discrepancy in algorithm comparison. This calls for a benchmark to compare the state-of-the-arts methods and evaluate their pros and cons.
Murong Wang   +4 more
openaire   +1 more source

Spherical Superpixel Segmentation

IEEE Transactions on Multimedia, 2018
These days, superpixel algorithms are widely used in computer vision and multimedia applications. However, existing algorithms are designed for planar images, which are less suited to deal with wide angle images. In this paper, we present a superpixel segmentation method for $\text{360}^\circ$ spherical images.
Qiang Zhao 0005   +5 more
openaire   +1 more source

Differential Evolutionary Superpixel Segmentation

IEEE Transactions on Image Processing, 2018
Superpixel segmentation has been of increasing importance in many computer vision applications recently. To handle the problem, most state-of-the-art algorithms either adopt a local color variance model or a local optimization algorithm. This paper develops a new approach, named differential evolutionary superpixels, which is able to optimize the ...
Yue-Jiao Gong, Yicong Zhou
openaire   +2 more sources

Bayesian Adaptive Superpixel Segmentation

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
Superpixels provide a useful intermediate image representation. Existing superpixel methods, however, suffer from at least some of the following drawbacks: 1) topology is handled heuristically; 2) the number of superpixels is either predefined or estimated at a prohibitive cost; 3) lack of adaptiveness.
Roy Uziel, Meitar Ronen, Oren Freifeld
openaire   +1 more source

Minimum barrier superpixel segmentation

Image and Vision Computing, 2018
Abstract Superpixel has become an essential processing unit in many computer vision systems, and superpixel segmentation of images is one of the most important step. In this paper, an efficient superpixel segmentation algorithm was proposed. We introduce a new compact-aware minimum barrier distance for superpixel segmentation (MBS), and a propagation
Yinlin Hu   +4 more
openaire   +1 more source

Entropy rate superpixel segmentation

CVPR 2011, 2011
We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters with similar sizes.
Ming-Yu Liu 0001   +3 more
openaire   +1 more source

ESNet: An Efficient Framework for Superpixel Segmentation

IEEE Transactions on Circuits and Systems for Video Technology
Sen Xu, Shikui Wei, Tao Ruan
exaly   +2 more sources

Dynamic Random Walk for Superpixel Segmentation

IEEE Transactions on Image Processing, 2020
In this paper, we propose a novel random walk model, called Dynamic Random Walk (DRW), which adds a new type of dynamic node to the original RW model and reduces redundant calculation by limiting the walk range. To solve the seed-lacking problem of the proposed DRW, we redefine the energy function of the original RW and use the first arrival ...
Xuejing Kang, Lei Zhu 0012, Anlong Ming
openaire   +2 more sources

Compressive Tracking based on Superpixel Segmentation

Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media, 2016
The compressive sensing trackers, which utilize a very sparse measurement matrix to capture the targets' appearance model, perform well when the tracked targets are well defined. However, such trackers often run into drifting problems due to the fact that the tracking result is a bounding box which also includes background information, especially in ...
Ting Chen 0004   +4 more
openaire   +2 more sources

Scene shape priors for superpixel segmentation

2009 IEEE 12th International Conference on Computer Vision, 2009
Unsupervised over-segmentation of an image into super-pixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feature vectors and as a starting point for the final segmentation. In this paper we investigate incorporating a priori information into superpixel segmentations.
Alastair Philip Moore   +4 more
openaire   +1 more source

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