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Check out the latest superpixel benchmark — Superpixel Benchmark (2016) — and let me know your opinion! @david_stutz

TAG»OPENCV«

SERIES»Working with Ubuntu«

LAPACKE_H_PATH-NOTFOUND when Installing OpenCV and Netbeans Links

This time in “Working with Ubuntu”: solving LAPACKE_H_PATH-NOTFOUND when installing OpenCV and some useful Netbeans plugins.

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ARTICLE

Running OpenCV and Google GLog with CMake on Travis CI

Running C++ projects on Travis CI may be challenging depending on the libraries used. Here I briefly describe how to run OpenCV and Google GLog on Travis CI.

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ARTICLE

Fast, Multi-Label Connected Components in MatLab

This article presents a MatLab MEX wrapper for a fast, multi-label connected components implementation in C++ originally written by Ali Rahimi.

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ARTICLE

Optical Flow I/O with OpenCV

This article presents an OpenCV wrapper for the Flow I/O code provided by the Sintel dataset [2].

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ARTICLE

Efficient Hierarchical Graph-Based Video Segmentation: An Implementation

This article presents an efficient implementation of the hierarchical graph-based video segmentation algorithm proposed by Grundmann et al. [1]. The implementation is available on GitHub.

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ARTICLE

Efficient High-Quality Superpixels: SEEDS Revised

SEEDS Revised is a new implementation of the superpixel algorithm SEEDS [1] used for evaluation in my bachelor thesis “Superpixel Segmentation using Depth Information”. This article introduces the basic concepts of SEEDS as well as the usage of SEEDS Revised.

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ARTICLE

Running VLFeat’s SLIC Superpixels using CMake and C++

There are several superpixel algorithms out there. One popular approach is called “Simple Linear Iterative Clustering” – short SLIC [1]. One implementation of SLIC is provided as part of the VLFeat library [2] which can be used from MatLab, but provides the C source code as well. This article shows how to use VLFeat’s implementation of SLIC from C++ using CMake.

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