Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis

Keywords

Computer science, Artificial intelligence, Scale-invariant feature transform, Subspace topology, Pattern recognition (psychology)

References

• Sparse Coding Of Time-Varying Natural ImagesBruno A. Olshausen — 2010
• Recognizing human actionsMubarak Shah — 2005
• A Comparison of Affine Region DetectorsKrystian Mikolajczyk, Tinne Tuytelaars, C. Schmid — 2005
• SENSC: a Stable and Efficient Algorithm for Nonnegative Sparse Coding: SENSC: a Stable and Efficient Algorithm for Nonnegative Sparse CodingLe Li, Yujin Zhang — 2009
• Evaluation of Local Spatio-temporal Features for Action RecognitionHeng Wang, Muhammad Muneeb Ullah, Alexander Kläser — 2009
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• On Space-Time Interest PointsIvan Laptev — 2005
• A Spatio-Temporal Descriptor Based on 3D-GradientsAlexander Klaeser, Marcin Marszałek, C. Schmid — 2008
• Unsupervised Learning of Human Action Categories Using Spatial-Temporal WordsJuan Carlos Niebles, Hesheng Wang, Hongcheng Wang — 2008
• Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortexJ. H. van Hateren, Daniel Ruderman — 1998
• A Biologically Inspired System for Action RecognitionHueihan Jhuang, T. Serre, Lior Wolf — 2007
• Recognizing realistic actions from videos “in the wild”Jingen Liu, Jiebo Luo, Mubarak Shah — 2009
• Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognitionMikel Rodríguez, Javed Ahmed, Mubarak Shah — 2008
• Independent component filters of natural images compared with simple cells in primary visual cortexJ. H. van Hateren, A. van der Schaaf — 1998
• Measuring Invariances in Deep NetworksIan Goodfellow, Honglak Lee, Quoc V. Le — 2009
• Speeded-Up Robust Features (SURF)Herbert Bay, Andreas Ess, Tinne Tuytelaars — 2008
• Large-scale deep unsupervised learning using graphics processorsRajat Raina, Anand Madhavan, Andrew Y. Ng — 2009
• Self-taught learning: transfer learning from unlabeled dataRajat Raina, Alexis Battle, Honglak Lee — 2007
• Object recognition from local scale-invariant featuresDavid Lowe — 1999
• Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature SubspacesAapo Hyvärinen, Patrik O. Hoyer — 2000

Cited by

• Scene Recognition by Manifold Regularized Deep Learning Architecture大洋 松尾, 洋治 中川, 昭和 中崎 — 2015
• Hierarchical Latent Concept Discovery for Video Event DetectionD Maxime — 2017
• Stacked Denoising Tensor Auto-Encoder for Action Recognition With Spatiotemporal CorruptionsМакеев Валерий Александрович — 2018
• Unsupervised feature learning for electronic nose data applied to Bacteria Identification in Blood.Martin Längkvist, Amy Loutfi — 2011
• Modèles structurés pour la reconnaissance d'actions dans des vidéos réalistesAdrien Gaidon — 2012
• Beyond histograms: why learned structure-preserving descriptors outperform HOGThomas Guthier, Volker Willert, Julian Eggert — 2014
• A Nonparametric Bayesian Approach toward Stacked Convolutional Independent Component AnalysisSotirios Chatzis, Dimitrios Kosmopoulos — 2014
• Graphical Models for Wide-Area Activity Analysis in Continuous VideosNandita M. Nayak — 2014
• Simultaneous Feature and Dictionary Learning for Image Set Based Face RecognitionJiwen Lu, Gang Wang, Jie Zhou — 2014
• Analyzing Complex Events and Human Actions in "in-the-wild" VideosHyungtae Lee — 2014
• 3D Robotic Sensing of People: Human Perception, Representation and Activity RecognitionHao Zhang — 2014
• 3D-Assisted Feature Synthesis for Novel Views of an ObjectHao Su, Fan Wang, Eric Yi — 2015
• Feature sampling and partitioning for visual vocabulary generation on large action classification datasetsMichael Sapienza, Fabio Cuzzolin, Philip H. S. Torr — 2014
• A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity RecognitionYago Sáez, Alejandro Baldominos, Pedro Isasi — 2016
• Feature Extraction and Recognition for Human Action RecognitionJiajia Luo — 2014
• Unsupervised Learning of Visual Representations Using VideosXiaolong Wang, Abhinav Gupta — 2015
• Learning representative and discriminative image representation by deep appearance and spatial codingBingyuan Liu, Jing Liu, Hanqing Lu — 2015
• Learning Temporal Embeddings for Complex Video AnalysisVignesh Ramanathan, Kevin Tang, Greg Mori — 2015
• Non-negative matrix completion for action detectionEhsan Adeli, Mahmood Fathy — 2015
• Modeling time-series with deep networksMartin Längkvist — 2014

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