# SMSLD

**Repository Path**: ZBingoWang/SMSLD

## Basic Information

- **Project Name**: SMSLD
- **Description**: Repository for the SMSLD descriptor
- **Primary Language**: Unknown
- **License**: BSD-4-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-12-13
- **Last Updated**: 2024-08-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

===== SOFTWARE =====

This software contains the SMSLD implementation as proposed by 
Bart Verhagen (barrie.verhagen@gmail.com), Radu Timofte (radu.timofte@esat.kuleuven.be) and 
Luc Van Gool (luc.vangool@esat.kuleuven.be). The current implementation
is based on the MSLD implementation of Zhiheng Wang (zhwang@nlpr.ia.ac.cn), 
Fuchao Wu and Zhanyi Hu.

This software contains the SMSLD descriptor. The SMSLD descriptor is a scale-invariant 
line segment descriptor for wide baseline matching. More info can be found in the paper
about SMSLD.

All comments can be addressed to the lead author.

===== Requirements =====
 - MATLAB
 - OpenCV
 - Preferably Microsoft Visual Studio

===== How to install =====
 - Change the *.props files in SMSLD/opencv to point to your openCV implementation.
 - Compile the SMSLD/SMSLD/SMSLD_Step2_Match/TianMatch.sln project using Visual Studio.
 - Change in matlab/workspace/testbench/SMSLD/testSMSLD.m and 
	matlab/workspace/testbench/SMSLD/benchmark.m the 'path_to_exe' variable to
	point to the binary created during the compilation of the TianMatch.sln project.
 - Run testSMSLD using matlab. 
Note: default the paths are set to run the test algorithms in the directory they exist.

===== Additional notes =====

The MSLD implementation on which the SMSLD implementation is based is unstable.
Rerunning the program a few times might give you the result in the end. Slightly changing
a parameter may help to stabilize.

If you are using this software, please quote our associated work:

Scale-invariant Line Descriptors for Wide Baseline Matching
by B. Verhagen, R. Timofte and L Van Gool.
published at 2014 IEEE Winter Conference on Applications of Computer Vision (WACV)
Copyright by IEEE