J
Janne Heikkilä
Researcher at University of Oulu
Publications - 235
Citations - 10626
Janne Heikkilä is an academic researcher from University of Oulu. The author has contributed to research in topics: Motion estimation & Image segmentation. The author has an hindex of 38, co-authored 229 publications receiving 9435 citations. Previous affiliations of Janne Heikkilä include University of Eastern Finland & Brigham and Women's Hospital.
Papers
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Proceedings ArticleDOI
A four-step camera calibration procedure with implicit image correction
Janne Heikkilä,Olli Silven +1 more
TL;DR: This paper presents a four-step calibration procedure that is an extension to the two-step method, and a linear method for solving the parameters of the inverse model is presented.
Book ChapterDOI
Blur Insensitive Texture Classification Using Local Phase Quantization
Ville Ojansivu,Janne Heikkilä +1 more
TL;DR: The classification accuracy of blurred texture images is much higher with the new method than with the well-known LBP or Gabor filter bank methods, and it is also slightly better for textures that are not blurred.
Journal ArticleDOI
Geometric camera calibration using circular control points
TL;DR: A calibration procedure for precise 3D computer vision applications is described that introduces bias correction for circular control points and a nonrecursive method for reversing the distortion model and indicates improvements in the calibration results in limited error conditions.
Book ChapterDOI
Segmenting salient objects from images and videos
TL;DR: A new salient object segmentation method, which is based on combining a saliency measure with a conditional random field (CRF) model, which outperforms the current state-of-the-art methods in both qualitative and quantitative terms.
Proceedings ArticleDOI
Recognition of blurred faces using Local Phase Quantization
TL;DR: Recognition of blurred faces using the recently introduced Local Phase Quantization (LPQ) operator is proposed and results show that the LPQ descriptor is highly tolerant to blur but still very descriptive outperforming LBP both with blurred and sharp images.