Towards a General Abstraction through Sequences of Conceptual Operations

Computer vision is a complex field which can be challenging for those outside the research community to apply in the real world. To address this we present a novel formulation for the abstraction of computer vision problems above algorithms, as part of our OpenVL framework. We have created a set of fundamental operations which form a basis from which we can build up descriptions of computer vision methods. We use these operations to conceptually define the problem, which we can then map into algorithm space to choose an appropriate method to solve the problem. We provide details on three of our operations, Match, Detect and Solve, and subsequently demonstrate the flexibility of description these three offer us. We describe various vision problems such as image registration and tracking through the sequencing of our operations and discuss how these may be extended to cover a larger range of tasks, which in turn may be used analogously to a graphics shader language.