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PERCOM
2010
ACM

All for one or one for all? Combining heterogeneous features for activity spotting

9 years 2 months ago
All for one or one for all? Combining heterogeneous features for activity spotting
Abstract—Choosing the right feature for motion based activity spotting is not a trivial task. Often, features derived by intuition or that proved to work well in previous work are used. While feature selection algorithms allow automatic decision, definition of features remains a manual task. We conduct a comparative study of features with very different origin. To this end, we propose a new type of features based on polynomial approximation of signals. The new feature type is compared to features used routinely for motion based activity recognition as well as to recently proposed body-model based features. Experiments were performed on three different, large datasets allowing a thorough, in-depth analysis. They not only show the respective strengths of the different feature types but also their complementarity resulting in improved performance through combination. It shows that each feature type with its individual and complementary strengths and weaknesses can improve results by co...
Ulf Blanke, Bernt Schiele, Matthias Kreil, Paul Lu
Added 29 Jan 2011
Updated 29 Jan 2011
Type Journal
Year 2010
Where PERCOM
Authors Ulf Blanke, Bernt Schiele, Matthias Kreil, Paul Lukowicz, Bernhard Sick, Thiemo Gruber
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