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Motion vector outlier removal using dissimilarity measure
Digital Signal Processing, 2015Abstract Global motion estimation, being one of the most important tools in video processing field with many applications, is mainly carried out in pixel or compressed domain. Since those based on the pixels have drawbacks such as high computational complexity, most researches are oriented to the compressed domain in which motion vectors are utilized.
Burak Yıldırım +1 more
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Removing Outliers Using The L\infty Norm
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06), 2006Recently, there has been interest in solving geometric vision problems such as triangulation and camera resectioning using L\infty minimization. One key advantage of using the L\infty norm rather than the L2 norm is that the L\infty cost function has a single minimum unlike the commonly used L2 cost function which typically has multiple local minima ...
K. Sim, R. Hartley
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Automated Outlier Removal for Mobile Microbenchmarking Datasets
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015Microbenchmarking is a useful tool for fine-grained performance analysis, and represents a potentially valuable tool in the development of mobile applications and systems. However, the fine-grained measurements of microbenchmarking are inherently susceptible to noise from the underlying operating system and hardware.
Adam Rehn, Jason Holdsworth, Ickai Lee
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Improving recommendation quality through outlier removal
International Journal of Machine Learning and Cybernetics, 2022Yuan-Yuan Xu, Shen-Ming Gu, Fan Min
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Outlier Removal for Fingerprinting Localization Methods
2022 56th Asilomar Conference on Signals, Systems, and Computers, 2022Brent Laird, Trac Tran
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Improving Classification by Outlier Detection and Removal
2015Most of the existing state-of-art techniques for outlier detection and removal are based upon density based clustering of given dataset. In this paper we have suggested a novel approach for iteratively pruning of outliers based upon the non-alignment with model created in a n-dimensional hyperspace.
Pankaj Kumar Sharma +2 more
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Removing Outliers in Illumination Estimation
Color and Imaging Conference, 2012Brian Funt, Milan Mosny
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Outlier Detection Based on Fuzzy Rough Granules in Mixed Attribute Data
IEEE Transactions on Cybernetics, 2022Zhong Yuan, Hongmei Chen, Trli30
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