Try MAXST AR Fusion Tracker Now ✨

title_eng.png

Visual SLAM Tool app is a object/space mapping tool that ensures more convenient utilization of Visual SLAM and Object Tracker functions of MAXST AR SDK

It uses Visual SLAM engine so it analyzes input from a camera and creates a point cloud based on extracted feature points. Therefore the richer the texture of an object is, the more precise the 3D map can be created.

Before creating a 3D map check whether your target object/space and environment is appropriate.

Select the Target object/space
Check the Mapping Environment


Select the Target Object/Space

  • Recommended Size of the Object/Space

    Visual SLAM Tool is optimized to create Medium Scale(0.3m-1.5m) objects and space 3D map.

    size.png

  • Select the Object/Space with Rich Texture texture.png

    Target with poor feature point or feature point that can be easily affected by the environment is not recommended.

    • Poor Textured Object: Object with simple shapes, smooth surfaces or repeating patterns has difficulty in creating 3D maps because of their poor feature point.
    • Non-Rigid Object: Non-Rigid object is not recommended because feature point can change during training or when recognizing objects.
    • Transparent Object: Transparent object can be trained with a background so feature point can change during training or when recognizing object.
    • Specular Object: Object that reflects light is not recommended because feature point change easily depending on the lighting.

Check the Mapping Environment

  • Select the Space

    Place the object in the empty space. space.png

  • Check the Light Condition

    Map your target under good light conditions. For example, a bright office and studio are recommended. In dark environments, the Visual SLAM Tool may not extract enough feature point to create a 3D map.

    Korean Copy 6.png

  • Check whether the Mapping Environment is Similar to Recognition Environment

    Set up your mapping environment in consideration of recognition one. If there's a big difference between the recognition environment and mapping environment, recognition may be difficult.