Computational analysis of visual motion
Computational analysis of visual motion
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct incremental model-based image motion segmentation for video analysis
Signal Processing - Video segmentation for content-based processing manipulation
Optical-Flow Estimation while Preserving Its Discontinuities: A Variational Approach
ACCV '95 Invited Session Papers from the Second Asian Conference on Computer Vision: Recent Developments in Computer Vision
JOINT SPACE-TIME MOTION-BASED SEGMENTATION OF IMAGE SEQUENCES WITH LEVEL SET PDES
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Variational Space-Time Motion Segmentation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Minimax Entropy Principle and Its Application to Texture Modeling
Neural Computation
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A multiphase level set framework for motion segmentation
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Simultaneous motion estimation and segmentation
IEEE Transactions on Image Processing
Motion segmentation by multistage affine classification
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Multiple motion segmentation with level sets
IEEE Transactions on Image Processing
A fast parametric motion estimation algorithm with illumination and lens distortion correction
IEEE Transactions on Image Processing
Object-based texture coding of moving video in MPEG-4
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision
A Continuous Labeling for Multiphase Graph Cut Image Partitioning
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A Statistical Overlap Prior for Variational Image Segmentation
International Journal of Computer Vision
Step-by-step description of lateral interaction in accumulative computation
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Embedding a region merging prior in level set vector-valued image segmentation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Effective level set image segmentation with a kernel induced data term
IEEE Transactions on Image Processing
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The purpose of this study is to investigate a variational method for joint segmentation and parametric estimation of image motion by basis function representation of motion and level set evolution. The functional contains three terms. One term is of classic regularization to bias the solution toward a segmentation with smooth boundaries. A second term biases the solution toward a segmentation with boundaries which coincide with motion discontinuities, following a description of motion discontinuities by a function of the image spatio-temporal variations. The third term refers to region information and measures conformity of the parametric representation of the motion of each region of segmentation to the image spatio-temporal variations. The components of motion in each region of segmentation are represented as functions in a space generated by a set of basis functions. The coefficients of the motion components considered combinations of the basis functions are the parameters of representation. The necessary conditions for a minimum of the functional, which are derived taking into consideration the dependence of the motion parameters on segmentation, lead to an algorithm which condenses to concurrent curve evolution, implemented via level sets, and estimation of the parameters by least squares within each region of segmentation. The algorithm and its implementation are verified on synthetic and real images using a basis of cosine transforms.