“VisionGL: Towards an API for Integrating Vision and Graphics” by Miller and Fels

  • ©Gregor Miller and Sidney Fels

  • ©Gregor Miller and Sidney Fels

  • ©Gregor Miller and Sidney Fels



Entry Number: 105


    VisionGL: Towards an API for Integrating Vision and Graphics



    Computer Vision and Computer Graphics have a long history of intersecting research, methods and applications. In general, it is the job of vision to extract a model from one or more images (and viewpoints) to represent some real-world object or scene. Graphics then takes this model and interprets it based on some context to render the model for visualization and interaction. There are many examples of this, such as avatar creation from KinectTM(extract depth and pose of person, mesh and render), panorama stitching in cameras (extract transforms among images and blend) and performance/ appearance capture. Recently we introduced OpenVL [Miller and Fels 2013], an abstraction for computer vision at a level such that general developers and researchers in other fields can apply sophisticated vision methods in their work. Other vision frameworks generally present APIs to developers as lists of specific computer vision techniques e.g. detection using Haar cascades. Application of these methods under real-world conditions requires significant algorithmic knowledge and a steep learning curve. OpenVL hides the details of algorithms behind an interface flexible enough to provide solutions to a wide variety of vision problems. Given this abstraction of vision, we would like to formulate an abstraction to perform graphics operations on the result of OpenVL.


    1. Miller, G., and Fels, S. 2013. OpenVL: A task-based abstraction for developer-friendly computer vision. In Proceedings of the 13th IEEE Workshop on the Applications of Computer Vision (WACV), WVM’13, IEEE, 288–295.


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