Particle animation and rendering using data parallel computation
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closed-Form Solutions for Physically Based Shape Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active vision
Depicting fire and other gaseous phenomena using diffusion processes
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Optical character recognition
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Particle Systems—a Technique for Modeling a Class of Fuzzy Objects
ACM Transactions on Graphics (TOG)
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
Tracking Deformable Objects in the Plane Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recurrent and concurrent neural networks for objects recognition
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Towards a measure of deformability of shape sequences
Pattern Recognition Letters
Capturing human activity by a curve
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Variation in object shape is an important visual cue for deformable object recognition and classification. In this paper, we present an approach to model gradual changes in the 2-D shape of an object. We represent 2-D region shape in terms of the spatial frequency content of the region contour using Fourier coefficients. The temporal changes in these coefficients are used as the temporal signatures of the shape changes. Specifically, we use autoregressive model of the coefficient series. We demonstrate the efficacy of the model on several applications. First, we use the model parameters as discriminating features for object recognition and classification. Second, we show the use of the model for synthesis of dynamic shape using the model learned from a given image sequence. Third, we show that, with its capability of predicting shape, the model can be used to predict contours of moving regions which can be used as initial estimates for the contour based tracking methods.