ViSP 3.1.0 main page

Table of Contents

• Introduction
• Software architecture
• Download
• Installation
• Tutorials
  • ViSP iOS
  • Installation from prebuild SDK
  • Installation from source
  • Installation from cross-compiling
  • Getting started
  • Image manipulation
  • Image processing
  • Camera calibration
  • Tracking
  • Detection
  • Computer vision
  • Visual servoing
  • Bridges over other frameworks
  • Other tools
• Using ViSP
• How to help ?

Introduction

ViSP [28] is a modular C++ library that allows fast development of visual servoing applications. ViSP is developed and maintained by the Inria Lagadic team located at Inria Rennes.

ViSP official site is https://visp.inria.fr

ViSP wiki is https://github.com/lagadic/visp/wiki

ViSP source code available on GitHub https://github.com/lagadic/visp

If you have any problems or find any bugs, please report them in the bug tracker. If you may need help, please use the available forums.

It is also possible to contact ViSP main developers using: visp@inria.fr

Software architecture

Since ViSP 3.0.0, we design a new modular software architecture where ViSP capabilities are grouped in several modules (core, io, gui, vision, …). In ViSP 3.1.0 we introduced a new module called imgproc. As a result, the user will find several shared or static libraries, one for each module. The following figure highlights the module dependencies and the third-party libraries that may be used by each module. The central module is the core module. All other modules depend on core.

ViSP modules and their optional dependencies

Download

From https://visp.inria.fr/download you can either download the latest stable release, a daily snapshot or the current development distribution using git.

Installation

Because ViSP is a multi platform library that works under Linux, OSX and Windows, to install ViSP you need the CMake configuration tool available from http://www.cmake.org. Furthermore, depending on your operation system and the capabilities (framegrabber, display, simulation, ...) you need, prior to install ViSP you may install third party libraries https://visp.inria.fr/software-architecture.

ViSP full installation procedure using CMake is detailed in the Installation from prebuild SDK tutorials and Installation from source tutorials. Getting started tutorials and documents in pdf are also available from https://visp.inria.fr/publications.

Tutorials

Here after you will find a list of tutorials that show the basic use of ViSP classes with a small first code.

ViSP iOS

• Tutorial: Installation from prebuilt packages for iOS devices
  In this tutorial you will learn how to install ViSP prebuilt framework for iOS devices.
• Tutorial: Installation from source for iOS devices
  In this tutorial you will learn how to install ViSP from source on OSX for iOS project.
• Tutorial: How to create a basic iOS application that uses ViSP
  This tutorial shows how to build a project that uses ViSP on iOS devices.
• Tutorial: Image processing on iOS
  This tutorial shows how to do simple image processing on iOS devices.
• Tutorial: AprilTag marker detection on iOS
  This tutorial shows how to do detct an AprilTag marker on iOS devices.

Installation from prebuild SDK

• Tutorial: Installation from prebuilt packages for Linux Ubuntu/Debian
  In this first tutorial you will learn how to install ViSP prebuilt SDK from Ubuntu or Debian packages.
• Tutorial: Installation from prebuilt packages for Arch Linux
  In this tutorial you will learn how to install ViSP prebuilt SDK for Arch Linux.
• Tutorial: Installation from prebuilt packages for OSX with Homebrew
  In this tutorial you will learn how to install ViSP prebuilt SDK on OSX with Homebrew.
• Tutorial: Installation from prebuilt packages for ROS
  In this tutorial you will learn how to install ViSP prebuilt SDK for ROS.

Installation from source

• Tutorial: Installation from source for Linux Ubuntu
  In this tutorial you will learn how to install ViSP from source on Linux Ubuntu.
• Tutorial: Installation from source for Linux Fedora
  In this other tutorial you will learn how to install ViSP from source on Linux Fedora.
• Tutorial: Installation from source for Linux CentOS
  In this other tutorial you will learn how to install ViSP from source on Linux CentOS.
• Tutorial: Installation from source for Linux openSUSE
  In this other tutorial you will learn how to install ViSP from source on Linux openSUSE.
• Tutorial: Installation from source for Raspberry Pi
  In this tutorial you will learn how to install ViSP from source on Raspberry Pi.
• Tutorial: Installation from source for Windows with Visual C++ 2012 (vc11)
  In this tutorial you will learn how to install ViSP from source on Windows 7 with Visual C++ 2012 (vc11).
• Tutorial: Installation from source for Windows with Visual C++ 2013 (vc12)
  In this tutorial you will learn how to install ViSP from source on Windows 10 with Visual C++ 2013 (vc12).
• Tutorial: Installation from source for Windows with Visual C++ 2015 (vc14)
  In this tutorial you will learn how to install ViSP from source on Windows 10 with Visual C++ 2015 (vc14).
• Tutorial: Installation from source for Windows with Visual C++ 2017 (vc15)
  In this tutorial you will learn how to install ViSP from source on Windows 10 with Visual C++ 2017 (vc15).
• Tutorial: Installation from source for Windows with Mingw-w64
  In this tutorial you will learn how to install ViSP from source on Windows 8.1 or Windows 10 with Mingw-w64.
• Tutorial: Installation from source for UWP with Visual C++ 2015 (vc14)
  In this tutorial you will learn how to install ViSP from source on Windows 10 for Universal Windows Platform apps with Visual C++ 2015 (vc14).
• Tutorial: Installation from source for UWP with Visual C++ 2017 (vc15)
  In this tutorial you will learn how to install ViSP from source on Windows 10 for Universal Windows Platform apps with Visual C++ 2017 (vc15).
• Tutorial: Installation from source for OSX with Homebrew
  In this tutorial you will learn how to install ViSP from source on OSX with Homebrew.

Installation from cross-compiling

• Tutorial: Cross-compilation for Raspberry Pi from Ubuntu host
  In this tutorial you will learn how to cross-compile ViSP on Ubuntu host for Raspberry Pi target.
• Tutorial: Cross-compilation for NAOqi OS from Ubuntu host
  In this tutorial you will learn how to cross-compile ViSP on Ubuntu host for NAOqi targets (NAO, Romeo, Pepper).

Getting started

• Tutorial: How to create and build a CMake project that uses ViSP on Unix or Windows
  This tutorial shows how to build a project that uses ViSP to read and display an image.
• Tutorial: How to create an application that uses ViSP on NAOqi OS
  This tutorial shows how to build a project that uses ViSP on NAOqi OS running on NAO, Romeo or Pepper humanoid robots.
• Tutorial: How to import a CMake project that uses ViSP in Eclipse IDE
  This tutorial shows how to import a CMake project that uses ViSP in Eclipse IDE.
• Tutorial: How to extend ViSP creating a new contrib module
  This tutorial explains how to exploit ViSP modular architecture in order to introduce a new contrib module.

Image manipulation

• Tutorial: How to display an image
  In this tutorial you will learn how to display an image in a window and how to down scale the window size to be able to display images that are larger than the screen resolution.
• Tutorial: Image frame grabbing
  This tutorial shows how to acquire images from a camera.
• Tutorial: Image filtering
  This tutorial shows how to filter an image with ViSP.
• Tutorial: Planar image projection
  This tutorial shows how to project the image of a planar scene to a given camera position.

Image processing

• Tutorial: Brightness and contrast adjustment
  This tutorial will show you some simple techniques to adjust or improve the brightness / contrast of an image.
• Tutorial: Contrast and image sharpening techniques
  This tutorial will show you some simple techniques to improve the contrast and the sharpness of an image.
• Tutorial: Automatic thresholding
  This tutorial will show you different methods to automatically threshold, binarize an image.
• Tutorial: Contours extraction from a binary image
  This tutorial will show you how to extract the contours from a binary image.
• Tutorial: Connected-components labeling
  This tutorial will show you how to do a connected-components labeling.
• Tutorial: Flood fill algorithm
  This tutorial will show you how to use the flood fill algorithm.
• Practical example: count the number of coins in an image
  This tutorial will show you how to count the number of coins in an image.

Camera calibration

• Tutorial: Camera calibration
  This tutorial explains how to calibrate a camera.

Tracking

• Tutorial: Blob tracking
  This tutorial introduces blob tracking and detection.
• Tutorial: Keypoint tracking
  This tutorial focuses on keypoint tracking using Kanade-Lucas-Tomasi feature tracker.
• Tutorial: Moving-edges tracking
  This tutorial focuses on line and ellipse tracking using moving-edges.
• Tutorial: Markerless model-based tracking
  This tutorial focuses on model-based trackers using either edges, keypoints or and hybrid scheme that uses edges and keypoints.
• Tutorial: Markerless model-based tracking with stereo cameras
  This tutorial focuses on model-based trackers with stereo cameras.
• Tutorial: Markerless generic model-based tracking
  This tutorial focuses on generic model-based trackers.
• Tutorial: Template tracking
  This tutorial focuses on template trackers based on image registration approaches.

Detection

• Tutorial: Keypoints matching
  This tutorial shows how to detect and match keypoints.
• Tutorial: Keypoint matching (deprecated)
  This tutorial shows how to detect and match SURF keypoints. It will be deprecated if you use an OpenCV version equal to 2.8.0 or a more recent version.
• Tutorial: Bar code detection
  This tutorial focuses on bar code (QR code, Data Matrix code) detection.
• Tutorial: Face detection
  This tutorial focuses on face detection thanks to OpenCV Haar cascade classifier.
• Tutorial: Object detection and localization
  This tutorial shows how to learn keypoints detected on a known object and how to use the matched correspondences to detect and estimate the pose of the object.
• Tutorial: AprilTag marker detection
  This tutorial focuses on AprilTag patterns detection and pose estimation.

Computer vision

• Tutorial: Pose estimation from points
  This tutorial focuses on pose estimation from planar or non planar points.
• Tutorial: Pose estimation from QRcode
  This tutorial focuses on pose estimation of a QRcode using it's four corners location.
• Tutorial: Homography estimation from points
  Here we explain how to estimate an homography from couples of matched points.
• Tutorial: Homography estimation from points (deprecated)
  Here we explain how to estimate an homography from couples of matched points. It will be deprecated if you use an OpenCV version equal to 2.8.0 or a more recent version.

Visual servoing

• Tutorial: Image-based visual servo
  This tutorial explains how to simulate an IBVS.
• Tutorial: Visual servo simulation on a pioneer-like unicycle robot
  This tutorial focuses on visual servoing simulation on a unicycle robot. The study case is a Pioneer P3-DX mobile robot equipped with a camera.
• Tutorial: How to boost your visual servo control law
  This tutorial explains how to speed up the time to convergence of a visual servo.

Bridges over other frameworks

• Tutorial: Bridge over OpenCV
  This tutorial explicit how to convert OpenCV to/from ViSP structures such as camera parameters, images...

Other tools

• Tutorial: Real-time curves plotter tool
  This tutorial explains how to plot curves in real-time during a visual servo.
• Tutorial: Debug and trace printings
  This tutorial explains how to introduce trace in the code that could be enabled for debugging or disabled.
• Tutorial: How to use multi-threading capabilities
  This tutorial explains how to implement multi-threaded applications to capture images from a camera in one thread and display these images in an other thread.

Using ViSP

ViSP C++ classes are organized in modules that may help the user during his project implementation.

From the example page, you will also find examples showing how to use the library to acquire and display an image, compute a camera pose, estimate an homography, servo a real robot or a simulated one using a 2D, 2D half or 3D visual servoing scheme, ...

How to help ?

ViSP library is an open source C++ library which is developed at Inria by Lagadic team. If you enjoy using ViSP, you may contribute to the project in different ways. This will motivate us to continue the efforts.

• You can submit a bug report using the tracker.
• You can submit patches or new functionalities using GitHub Pull Request mechanism.
• You can write new tutorials, new documentations or simply improve the existing documentation.
• If you just want to say you've been happy with the library, you can send us a postcard from your place, to the following address: Inria Rennes Bretagne Atlantique, Lagadic team, Campus de Beaulieu, 35042 Rennes Cedex, FRANCE.

You can also ask for help using either the french or the english forum.