Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Actions Sketch: A Novel Action Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
International Journal of Computer Vision
Successive Convex Matching for Action Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scene segmentation based on IPCA for visual surveillance
Neurocomputing
ASIFT: A New Framework for Fully Affine Invariant Image Comparison
SIAM Journal on Imaging Sciences
Recovering human body configurations: combining segmentation and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Signal Processing - Part II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Human Gait Recognition With Matrix Representation
IEEE Transactions on Circuits and Systems for Video Technology
Online RGB-D gesture recognition with extreme learning machines
Proceedings of the 15th ACM on International conference on multimodal interaction
Neural networks letter: Comments on the "No-Prop" algorithm
Neural Networks
Hi-index | 0.01 |
This paper introduces a novel recognition framework for human actions using hybrid features. The hybrid features consist of spatio-temporal and local static features extracted using motion-selectivity attribute of 3D dual-tree complex wavelet transform (3D DT-CWT) and affine SIFT local image detector, respectively. The proposed model offers two core advantages: (1) the framework is significantly faster than traditional approaches due to volumetric processing of images as a '3D box of data' instead of a frame by frame analysis, (2) rich representation of human actions in terms of reduction in artifacts in view of the promising properties of our recently designed full symmetry complex filter banks with better directionality and shift-invariance properties. No assumptions about scene background, location, objects of interest, or point of view information are made whereas bidirectional two-dimensional PCA (2D-PCA) is employed for dimensionality reduction which offers enhanced capabilities to preserve structure and correlation amongst neighborhood pixels of a video frame.