Sparse Modeling of Human Actions from Motion Imagery

Alexey Castrodad1, Guillermo Sapiro1
1Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455 USA

Tóm tắt

Từ khóa


Tài liệu tham khảo

Aharon, M., Elad, M., & Bruckstein, A. (2006). K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 54(11), 4311–4322.

Blake, R., & Shiffrar, M. (2007). Perception of human motion. Annual Review of Psychology, 58(1), 47–73.

Bruckstein, A., Donoho, D., & Elad, M. (2009). From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Review, 51(1), 34–81.

Cadieu, C., & Olshausen, B. A. (2008). Learning transformational invariants from natural movies. In NIPS (pp. 209–216).

Castrodad, A., Xing, Z., Greer, J., Bosch, E., Carin, L., & Sapiro, G. (2011). Learning discriminative sparse representations for modeling, source separation, and mapping of hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 49(11), 4263–4281.

Charles, A., Olshausen, B., & Rozell, C. (2011). Learning sparse codes for hyperspectral imagery. IEEE Journal of Selected Topics in Signal Processing.

Chen, C., Ryoo, M. S., & Aggarwal, J. K. (2010). UT-Tower dataset: aerial view activity classification challenge. http://cvrc.ece.utexas.edu/SDHA2010/Aerial_View_Activity.html .

Dalal, N., & Triggs, B. (2006). Human detection using oriented histograms of flow and appearance. In ECCV.

Dean, T., Washington, R., & Corrado, G. (2009). Recursive sparse, spatiotemporal coding. In ISM (pp. 645–650).

Dollar, P., Rabaud, V., Cottrell, G., & Belongie, S. (2005). 2nd joint IEEE international workshop on behavior recognition via sparse spatio-temporal features. In Visual surveillance and performance evaluation of tracking and surveillance (pp. 65–72).

Donoho, D. L. (2000). High-dimensional data analysis: the curses and blessings of dimensionality. In American Mathematical Society conference math challenges of the 21st century.

Gall, J., Yao, A., Razavi, N., van Gool, L., & Lempitsky, V. (2011). Hough forests for object detection, tracking, and action recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(11), 2188–2202.

Gregor, K., & LeCun, Y. (2010). Learning fast approximations of sparse coding. In ICML (pp. 399–406).

Guo, K., Ishwar, P., & Konrad, J. (2010). Action recognition using sparse representation on covariance manifolds of optical flow. In AVSS (pp. 188–195).

Ikizler-Cinbis, N., & Sclaroff, S. (2010). Object, scene and actions: combining multiple features for human action recognition. In ECCV (pp. 494–507).

Jhuang, H., Serre, T., Wolf, L., & Poggio, T. (2007). A biologically inspired system for action recognition. In ICCV (pp. 1–8).

Kläser, A., Marszałek, M., & Schmid, C. (2008). A spatio-temporal descriptor based on 3d-gradients. In BMVC.

Kovashka, A., & Grauman, K. (2010). Learning a hierarchy of discriminative space-time neighborhood features for human action recognition. In CVPR (pp. 2046–2053).

Laptev, I., & Lindeberg, T. (2003). Space-time interest points. In ICCV (pp. 432–439).

Laptev, I., Marszałek, M., Schmid, C., & Rozenfeld, B. (2008). Learning realistic human actions from movies. In CVPR.

Le, Q., Zou, W., Yeung, S., & Ng, A. (2011). Learning hierarchical spatio-temporal features for action recognition with independent subspace analysis. In CVPR.

Liu, J., Luo, J., & Shah, M. (2009). Recognizing realistic actions from videos “in the wild”. In CVPR.

Mairal, J., Bach, F., Ponce, J., Sapiro, G., & Zisserman, A. (2008). Supervised dictionary learning. In NIPS (pp. 1033–1040).

Mairal, J., Bach, F., Ponce, J., & Sapiro, G. (2010). Online learning for matrix factorization and sparse coding. Journal of Machine Learning Research, 11, 19–60.

Marszałek, M., Laptev, I., & Schmid, C. (2009). Actions in context. In CVPR.

Ramirez, I., Sprechmann, P., & Sapiro, G. (2010). Classification and clustering via dictionary learning with structured incoherence and shared features. In CVPR (pp. 3501–3508).

Rodriguez, M. D., Ahmed, J., & Shah, M. (2008). Action Mach: a spatio-temporal maximum average correlation height filter for action recognition. In CVPR.

Ryoo, M., Chen, C., Aggarwal, J., & Chowdhury, R. A. (2010). An overview of contest on semantic description of human activities (sdha) 2010. In ICPR-contests (pp. 270–285).

Schuldt, C., Laptev, I., & Caputo, B. (2004). Recognizing human actions: a local svm approach. In ICPR (pp. 32–36).

Scovanner, P., Ali, S., & Shah, M. (2007). A 3-dimensional sift descriptor and its application to action recognition. In ACM multimedia (pp. 357–360).

Shao, L., & Mattivi, R. (2010). Feature detector and descriptor evaluation in human action recognition. In CIVR (pp. 477–484).

Sprechmann, P., & Sapiro, G. (2010). Dictionary learning and sparse coding for unsupervised clustering. In ICASSP.

Taylor, G., Fergus, R., Le Cun, Y., & Bregler, C. (2010). Convolutional learning of spatio-temporal features. In ECCV (pp. 140–153).

Tibshirani, R. (1994). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society, Series B, 58, 267–288.

Vezzani, R., Davide, B., & Cucchiara, R. (2010). HMM based action recognition with projection histogram features. In ICPR (pp. 286–293).

Wang, H., Ullah, M. M., Kläser, A., Laptev, I., & Schmid, C. (2009). Evaluation of local spatio-temporal features for action recognition. In BMVC.

Wang, H., Kläser, A., Schmid, C., & Cheng-Lin, L. (2011). Action recognition by dense trajectories. In CVPR (pp. 3169–3176).

Willems, G., Tuytelaars, T., & van Gool, L. (2008). An efficient dense and scale-invariant spatio-temporal interest point detector. In ECCV (pp. 650–663).

Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2008). Robust face recognition via sparse representation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(2), 210–227.

Xiang, Z., Xu, H., & Ramadge, P. (2011). Learning sparse representations of high dimensional data on large scale dictionaries. In NIPS (pp. 900–908).

Yeffet, L., & Wolf, L. (2009). Local trinary patterns for human action recognition. In ICCV (pp. 492–497).