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Space-Time Signal Analysis and the 3D Shearlet Transform.

, , and . Journal of Mathematical Imaging and Vision, 60 (7): 1008-1024 (2018)

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A Sparsity-Enforcing Method for Learning Face Features., , , and . IEEE Trans. Image Processing, 18 (1): 188-201 (2009)Hausdorff Kernel for 3D Object Acquisition and Detection., , and . ECCV (4), volume 2353 of Lecture Notes in Computer Science, page 20-33. Springer, (2002)Structured Multi-class Feature Selection for Effective Face Recognition., , , and . ICIAP (1), volume 8156 of Lecture Notes in Computer Science, page 410-419. Springer, (2013)Spatio-temporal constraints for on-line 3D object recognition in videos., , and . Comput. Vis. Image Underst., 113 (12): 1198-1209 (2009)A Regularized Framework for Feature Selection in Face Detection and Authentication., , , and . Int. J. Comput. Vis., 83 (2): 164-177 (2009)Mean BoF per Quadrant - Simple and Effective Way to Embed Spatial Information in Bag of Features., and . VISAPP (2), page 297-304. SciTePress, (2015)Space-Time Signal Analysis and the 3D Shearlet Transform., , and . Journal of Mathematical Imaging and Vision, 60 (7): 1008-1024 (2018)Keep it simple and sparse: real-time action recognition., , , and . J. Mach. Learn. Res., 14 (1): 2617-2640 (2013)The complexity of biological motion., , , , , and . ICDL-EPIROB, page 66-71. IEEE, (2016)Background modeling through dictionary learning., , , and . ICIP, page 2524-2528. IEEE, (2013)