]> 2026-04-04T14:37:50+02:00 Publications:Illuminance Flow Estimation by Regression 500 en <p>We investigate the estimation of illuminance flow using Histograms of Oriented Gradient features (HOGs). In a regression setting, we found for both ridge regression and support vector machines, that the optimal solution shows close resemblance to the gradient based structure tensor (also known as the second moment matrix). Theoretical results are presented showing in detail how the structure tensor and the HOGs are connected. This relation will benefit computer vision tasks such as affine invariant texture/object matching using HOGs. Several properties of HOGs are presented, among others, how many bins are required for a directionality measure, and how to estimate HOGs through spatial averaging that requires no binning.</p> http://dx.doi.org/10.1007/s11263-010-0353-7 http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:537591 312 3 International Journal of Computer Vision Journal Paper 304 Illuminance Flow Estimation by Regression 90 2010 2016-09-30T20:40:17Z 2457662.3613079 Illuminance Flow Estimation by Regression 500 0 plainlist list 1 [[:Publications:Illuminance Flow Estimation by Regression]] Illuminance Flow Estimation by Regression# QUERY10f9bd5620def000f0a0a5fc4ec277aa 500 [2,"smw-datavalue-property-restricted-annotation-use","Publisher"] Illuminance Flow Estimation by Regression# ERR6c155b5d70b69ddb590b4f2e73389c2a 500 [2,"smw-datavalue-property-restricted-annotation-use","Author"] Illuminance Flow Estimation by Regression# ERRe24f17e090c98448f3de99d03182b7b6