Active vision
Motion planning using image divergence and deformation
Active vision
A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
Generating spatiotemporal models from examples
BMVC '95 Proceedings of the 6th British conference on Machine vision (Vol. 2)
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A Modified Version of the K-Means Algorithm with a Distance Based on Cluster Symmetry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Tracking via Level Set PDEs without Motion Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Intensity and Motion for Incremental Segmentation and Tracking Over Long Image Sequences
ECCV '92 Proceedings of the Second European Conference on 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
Learning Dynamics of Complex Motions from Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Real-Time Lip Tracking for Audio-Visual Speech Recognition Applications
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Segmentation of moving objects by robust motion parameter estimation over multiple frames
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Dense Nonrigid Motion Tracking from a Sequence of Velocity Fields
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SVM-KM: Speeding SVMs Learning with a priori Cluster Selection and k-Means
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
A recursive filter for phase velocity assisted shape-based tracking of cardiac non-rigid motion
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Region tracking through image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Tracking medical 3D data with a parametric deformable model
ISCV '95 Proceedings of the International Symposium on Computer Vision
Wormholes in Shape Space: Tracking through Discontinuous Changes in Shape
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic active regions and level set methods for motion estimation and tracking
Computer Vision and Image Understanding
Deformable object tracking using the boundary element method
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Probabilistic tracking in joint feature-spatial spaces
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Fast object tracking in digital video
IEEE Transactions on Consumer Electronics
IEEE Transactions on Image Processing
Finding out general tendencies in speckle noise reduction in ultrasound images
Expert Systems with Applications: An International Journal
Segmentation of 3D brain structures using the Bayesian generalized fast marching method
BI'10 Proceedings of the 2010 international conference on Brain informatics
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A novel Gaussian mixture model (GMM)-based region and gradient active contour model is proposed for general object boundary tracking and the purpose of boundary tracking for anal muscle layers. Motion information is extracted from adjacent slice and is used to guide the first step of boundary tracking procedure. The idea is that GMM is introduced into the statistical feature computation for object region and background region, thereby providing an accurate model for regional pixel intensity description. Expectation-maximization algorithm and K-means algorithm are used for parameter solutions of GMM. Based on the available region information, gradient information and the self-constraints of the contour, a unifying active contour model is proposed. The proposed active contour models and tracking algorithm were tested on synthetic images and simulated ultrasound images to evaluate some generic features of the model for boundary tracking. Furthermore, it was applied to perform boundary tracking of anal muscle layers. The tracking results were evaluated by three experts. The results showed that the proposed method has a good performance for boundary tracking on anal wall ultrasound image.