Finding Trajectories of Feature Points in a Monocular Image Sequence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust model-based motion tracking through the integration of search and estimation
International Journal of Computer Vision
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Embedding Gestalt Laws in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Deformable Objects in the Plane Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '90 Proceedings of the First European Conference on Computer Vision
Boundary extraction in thermal images by edge map
Proceedings of the 2004 ACM symposium on Applied computing
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving Performance of Distribution Tracking through Background Mismatch
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Tracking via HMMF in Joint Feature-Spatial Space
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Geodesic active regions and level set methods for motion estimation and tracking
Computer Vision and Image Understanding
Traffic object detections and its action analysis
Pattern Recognition Letters
Object tracking using mean shift and active contours
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Computer Vision and Image Understanding
Parametric model-based motion segmentation using surface selection criterion
Computer Vision and Image Understanding
ACM Computing Surveys (CSUR)
Moving object tracking under varying illumination conditions
Pattern Recognition Letters
Affine and projective active contour models
Pattern Recognition
Facial boundary detection with an active contour model
Pattern Recognition Letters
A Framework for Model-Based Tracking Experiments in Image Sequences
International Journal of Computer Vision
Stability and convergence of the level set method in computer vision
Pattern Recognition Letters
Tracking Deforming Objects Using Particle Filtering for Geometric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Properties of orthogonal Gaussian-Hermite moments and their applications
EURASIP Journal on Applied Signal Processing
A Variational Technique for Time Consistent Tracking of Curves and Motion
Journal of Mathematical Imaging and Vision
Anisotropic virtual electric field for active contours
Pattern Recognition Letters
Track and cut: simultaneous tracking and segmentation of multiple objects with graph cuts
Journal on Image and Video Processing - Video Tracking in Complex Scenes for Surveillance Applications
An extension of min/max flow framework
Image and Vision Computing
IEEE Transactions on Circuits and Systems for Video Technology
Computer Vision and Image Understanding
Parametric model-based motion segmentation using surface selection criterion
Computer Vision and Image Understanding
Geodesic active regions and level set methods for motion estimation and tracking
Computer Vision and Image Understanding
A fast and robust feature-based 3D algorithm using compressed image correlation
Pattern Recognition Letters
Lip contour extraction using level set curve evolution with shape constraint
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Gradient vector flow active contours with prior directional information
Pattern Recognition Letters
Visual tracking by hypothesis testing
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Joint tracking and segmentation of objects using graph cuts
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Interactive rotoscoping: extracting and tracking object sketch
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Contour tracking with abrupt motion
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Deform PF-MT: particle filter with mode tracker for tracking nonaffine contour deformations
IEEE Transactions on Image Processing
Multiphase joint segmentation-registration and object tracking for layered images
IEEE Transactions on Image Processing
Visual tracking using the Earth Mover's Distance between Gaussian mixtures and Kalman filtering
Image and Vision Computing
An object tracking scheme based on local density
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Multiregion level set tracking with transformation invariant shape priors
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Tracking objects using shape context matching
Neurocomputing
A variational approach for object contour tracking
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
An improved real-time contour tracking algorithm using fast level set method
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Real time hand tracking based on active contour model
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Shape based appearance model for kernel tracking
Image and Vision Computing
A novel framework for motion segmentation and tracking by clustering incomplete trajectories
Computer Vision and Image Understanding
Hi-index | 0.14 |
Tracking regions in an image sequence is a challenging and difficult problem in image processing and computer vision and at the same time, one that has many important applications: automated video surveillance, video database search and retrieval, automated video editing, etc. So far, numerous approaches to region tracking have been proposed. Many of them suffer from excessive constraints imposed on the motion of the region being tracked and need an explicit motion model (e.g., affine, Euclidean). Some, which do not need a parametrized motion model, rely instead on a dense motion field. By and large, most rely on some kind or other of motion information. Those which do not use any motion information instead use a model of the region being tracked, typically by assuming strong intensity boundaries, or constraining the shape of the region to belong to a parametrized family of shapes. In this paper, we propose a novel approach to region tracking that is derived from a Bayesian formulation. The novelty of the approach is twofold: First, no motion field or motion parameters need to be computed. This removes a major burden since accurate motion computation has been and remains a challenging problem and the quality of region tracking algorithms based on motion critically depends on the computed motion fields and parameters. The second novelty of this approach, is that very little a priori information about the region being tracked is used in the algorithm. In particular, unlike numerous tracking algorithms, no assumption is made on the strength of the intensity edges of the boundary of the region being tracked, nor is its shape assumed to be of a certain parametric form. The problem of region tracking is formulated as a Bayesian estimation problem and the resulting tracking algorithm is expressed as a level set partial differential equation. We present further extensions to this partial differential equation, allowing the possibility of including additional information in the tracking process, such as priors on the region's intensity boundaries and we present the details of the numerical implementation. Very promising experimental results are provided using numerous real image sequences with natural object and camera motion.