A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmenting focused objects in complex visual images
Pattern Recognition Letters
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Statistical Region Snake-Based Segmentation Adapted to Different Physical Noise Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Multiresolution Segmentation for Images with Low Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense Structure-from-Motion: An Approach Based on Segment Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Color active shape models for tracking non-rigid objects
Pattern Recognition Letters - Special issue: Colour image processing and analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation and Tracking of Faces in Color Images
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Tracking Objects Using Density Matching and Shape Priors
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Multiresolution 3-D range segmentation using focus cues
IEEE Transactions on Image Processing
Objective evaluation of video segmentation quality
IEEE Transactions on Image Processing
RAGS: region-aided geometric snake
IEEE Transactions on Image Processing
Performance measures for video object segmentation and tracking
IEEE Transactions on Image Processing
Video object tracking with feedback of performance measures
IEEE Transactions on Circuits and Systems for Video Technology
Spatiotemporal region enhancement and merging for unsupervized object segmentation
Journal on Image and Video Processing
Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS)
Journal of Visual Communication and Image Representation
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Two new region-based methods for video object tracking using active contours are presented. The first method is based on the assumption that the color histogram of the tracked object is nearly stationary from frame to frame. The proposed method is based on minimizing the color histogram difference between the estimated objects at a reference frame and the current frame using a dynamic programming framework. The second method is defined for scenes where there is an out-of-focus blur difference between the object of interest and the background. In such scenes, the proposed ''defocus energy'' can be utilized for automatic segmentation of the object boundary, and it can be combined with the histogram method to track the object more efficiently. Experiments demonstrate that the proposed methods are successful in difficult scenes with significant background clutter.