1 research outputs found
Using Barriers to Reduce the Sensitivity to Edge Miscalculations of Casting-Based Object Projection Feature Estimation
3D motion tracking is a critical task in many computer vision applications.
Unsupervised markerless 3D motion tracking systems determine the most relevant
object in the screen and then track it by continuously estimating its
projection features (center and area) from the edge image and a point inside
the relevant object projection (namely, inner point), until the tracking fails.
Existing reliable object projection feature estimation techniques are based on
ray-casting or grid-filling from the inner point. These techniques assume the
edge image to be accurate. However, in real case scenarios, edge
miscalculations may arise from low contrast between the target object and its
surroundings or motion blur caused by low frame rates or fast moving target
objects. In this paper, we propose a barrier extension to casting-based
techniques that mitigates the effect of edge miscalculations.Comment: arXiv admin note: substantial text overlap with arXiv:1202.6586v1 and
arXiv:1111.396