Titlebook: Computer Vision -- ECCV 2014; 13th European Confer David Fleet,Tomas Pajdla,Tinne Tuytelaars Conference proceedings 2014 Springer Internati

Iatrogenic

ONYM

Spectra Estimation of Fluorescent and Reflective Scenes by Using Ordinary Illuminants, we propose a novel four-parameter model to express absorption and emission spectra, which is more compact and discriminative than the linear model. Based on this model, we present an absorption spectra estimation method in the presence of three illuminations. The correctness and accuracy of our pr

合同

类似思想

打火石

https://doi.org/10.1057/9781137322630spatial processing of standard opponent colour spaces, and these are the first chromatic descriptors that appear to achieve such performance levels individually. For all stages, parametrisations are suggested that allow successful optimisation using categorization performance as an objective. Classi

Cardioversion

debunk

Governing the Power of Proprietors,standing performance with respect to the state-of-the-art trackers. We illustrate quantitative and qualitative performance of our algorithm in all the sequences in tracking benchmark and other challenging videos.

wangle

Cambridge Imperial and Post-Colonial Studiesns. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.

braggadocio

https://doi.org/10.1007/978-1-4419-6685-8ndling logic, is evaluated on two challenging data-sets containing 50 sequences each. The first is a recently published benchmark where ELK ranks 3rd among 30 tracking methods evaluated. On the second data-set of vehicles undergoing severe view point changes ELK ranks in 1st place outperforming stat

Compass

Olaf Prante,Miriam Dörfler,Peter Gmeinerly coherent regions and the quality of estimated motion is improved by avoiding motion smoothing across regions with different labels. We evaluate our algorithm with challenging video sequences and present significant performance improvement over the state-of-the-art techniques quantitatively and qu