@INPROCEEDINGS{5470597, author = {Blanke, Ulf and Schiele, Bernt and Kreil, Matthias and Lukowicz, Paul and Sick, Bernhard and Gruber, Thiemo}, title = {{All for one or one for all? Combining Heterogeneous Features for Activity Spotting}}, booktitle = {Workshop Proceedings of the 8th International Conference on Pervasive Computing and Communications (PerCom Workshops)}, year = {2010}, pages = {18--24}, month = mar#"--"#apr, location = {Mannheim, Germany}, 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 combination.}, doi = {10.1109/PERCOMW.2010.5470597}, keywords = {feature extraction;image motion analysis;image recognition;image sensors;polynomial approximation;wearable computers;body-model based features;feature selection;heterogeneous features;motion based activity recognition;motion based activity spotting;signal polynomial approximation;wearable computing;wearable sensor;Boosting;Computational intelligence;Computer science;Embedded computing;Embedded system;Frequency;Intelligent systems;Performance analysis;Polynomials;Wearable sensors;activity recognition;feature analysis;wearable computing}, }