Fundamentals of digital image processing
Fundamentals of digital image processing
Fundamentals of speech recognition
Fundamentals of speech recognition
Automatic symbolic traffic scene analysis using belief networks
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
A framework for recognizing multi-agent action from visual evidence
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
View-Invariant Representation and Recognition of Actions
International Journal of Computer Vision
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Towards a View Invariant Gait Recognition Algorithm
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
ASL Recognition Based on a Coupling Between HMMs and 3D Motion Analysis
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Recognition of Group Activities using Dynamic Probabilistic Networks
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Large-Scale Event Detection Using Semi-Hidden Markov Models
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognition of two-person interactions using a hierarchical Bayesian network
IWVS '03 First ACM SIGMM international workshop on Video surveillance
On the use of Anthropometry in the Invariant Analysis of Human Actions
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Shape Analysis: Clustering, Learning, and Testing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploring the Space of a Human Action
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
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Gait Recognition by Gait Dynamics Normalization
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Function Space of an Activity
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Joint Recognition of Complex Events and Track Matching
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Automatic Discovery of Action Taxonomies from Multiple Views
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Free viewpoint action recognition using motion history volumes
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Unsupervised view and rate invariant clustering of video sequences
Computer Vision and Image Understanding
Performance analysis of time-distance gait parameters under different speeds
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Identification of humans using gait
IEEE Transactions on Image Processing
MPCA: Multilinear Principal Component Analysis of Tensor Objects
IEEE Transactions on Neural Networks
Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Aligning spatio-temporal signals on a special manifold
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Robust Gait Recognition by Learning and Exploiting Sub-gait Characteristics
International Journal of Computer Vision
Computer Vision and Image Understanding
Human action recognition using multiple views: a comparative perspective on recent developments
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Image and Vision Computing
Fitting smoothing splines to time-indexed, noisy points on nonlinear manifolds
Image and Vision Computing
Advances in matrix manifolds for computer vision
Image and Vision Computing
Pattern Recognition Letters
Generative models for functional data using phase and amplitude separation
Computational Statistics & Data Analysis
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Pattern recognition in video is a challenging task because of the multitude of spatio-temporal variations that occur in different videos capturing the exact same event. While traditional pattern-theoretic approaches account for the spatial changes that occur due to lighting and pose, very little has been done to address the effect of temporal rate changes in the executions of an event. In this paper, we provide a systematic model-based approach to learn the nature of such temporal variations (time warps) while simultaneously allowing for the spatial variations in the descriptors. We illustrate our approach for the problem of action recognition and provide experimental justification for the importance of accounting for rate variations in action recognition. The model is composed of a nominal activity trajectory and a function space capturing the probability distribution of activity-specific time warping transformations.We use the square-root parameterization of time warps to derive geodesics, distance measures, and probability distributions on the space of time warping functions. We then design a Bayesian algorithm which treats the execution rate function as a nuisance variable and integrates it out using Monte Carlo sampling, to generate estimates of class posteriors. This approach allows us to learn the space of time warps for each activity while simultaneously capturing other intra- and interclass variations. Next, we discuss a special case of this approach which assumes a uniform distribution on the space of time warping functions and show how computationally efficient inference algorithms may be derived for this special case. We discuss the relative advantages and disadvantages of both approaches and show their efficacy using experiments on gait-based person identification and activity recognition.