Maxim Karpushin

2 accepted papers

2017

Good features to track for RGBD images

Maxim Karpushin, Giuseppe Valenzise, Frédéric Dufaux

ICASSP 2017accepted

RGBD (texture-plus-depth) image representation enriches traditional 2D content with additional geometrical information, having the potential to improve the performance of many computer vision tasks. In image matching, this has been partially studied by considering how depth maps can help render feat…

Cited by 0 Source ↗Scholar ↗

2016

An image smoothing operator for fast and accurate scale space approximation

Maxim Karpushin, Giuseppe Valenzise, Frédéric Dufaux

ICASSP 2016accepted

Gussian image smoothing is a fundamental operation in the extraction of scale-invariant feature points. Its computation, however, can be too expensive in some resource-constrained scenarios. Alternative solutions such as the box filter can be computed more efficiently, at the cost of a loss in featu…

Cited by 10 Source ↗Scholar ↗