Elements of information theory
Elements of information theory
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Parameterized modeling and recognition of activities
Computer Vision and Image Understanding
Robust Real-Time Periodic Motion Detection, Analysis, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Learning variable-length Markov models of behavior
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Human Activity Recognition Using Multidimensional Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenGait: Motion-Based Recognition of People Using Image Self-Similarity
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Gait Identification Challenge Problem: Data Sets and Baseline Algorithm
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Unsupervised Learning of Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated derivation of behavior vocabularies for autonomous humanoid motion
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Silhouette-Based Human Identification from Body Shape and Gait
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Gait Analysis for Recognition and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fusion of Static and Dynamic Body Biometrics for Gait Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generative modeling for continuous non-linearly embedded visual inference
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Priors for People Tracking from Small Training Sets
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Conditional Random Fields for Contextual Human Motion Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
The Function Space of an Activity
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Abnormal Walking Gait Analysis Using Silhouette-Masked Flow Histograms
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Probabilistic expression analysis on manifolds
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Appearance manifold of facial expression
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Identification of humans using gait
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Recognizing Human Actions Using Silhouette-based HMM
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Human action recognition using boosted EigenActions
Image and Vision Computing
A survey on vision-based human action recognition
Image and Vision Computing
Histograms of optical flow for efficient representation of body motion
Pattern Recognition Letters
Pedestrian gait classification based on Hidden Markov models
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Human action recognition based on tracking features
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Human action recognition based on random spectral regression
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Human action recognition using spatio-temporal classification
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Human action recognition based on graph-embedded spatio-temporal subspace
Pattern Recognition
Human action segmentation and classification based on the Isomap algorithm
Multimedia Tools and Applications
Common-sense reasoning for human action recognition
Pattern Recognition Letters
Shape classification by manifold learning in multiple observation spaces
Information Sciences: an International Journal
Hi-index | 0.00 |
Human motion analysis is increasingly attracting much attention from computer vision researchers. This paper aims to address the task of human gait and activity analysis from image sequences by learning and recognition of sequential data under a general integrated framework. Human movements generally exhibit intrinsically nonlinear spatiotemporal characteristics in the high-dimensional ambient space. An attractive framework, which we explore here, is to: (1) Extract simple and reliable features from image sequences. (2) Find a low-dimensional feature representation embedded in high-dimensional image data. (3) Then characterize/classify the motions in this low-dimensional feature space. We examine two simple alternatives for step 1: silhouette and a distance transformed silhouette; and three quite different methods for step 3: Gaussian mixture models (GMM) based classification, a matching-based approach with the mean Hausdorff distance, and continuous hidden Markov models (HMM) based modelling and recognition. The core is step 2 where we choose to use LPP (locality preserving projections), an optimal linear approximation to a nonlinear spectral embedding technique (i.e., Laplacian eigenmap). In essence our aim is to see whether this core, together with simple approaches to steps 1 and 3, can solve problems across several types of human gait and activity. To see how well the proposed framework performs, we carry out extensive experiments in three related domains: human activity recognition, abnormal gait analysis, and gait-based human identification. The experimental results show that the proposed framework performs well across all three areas.