Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Motion segmentation and qualitative dynamic scene analysis from an image sequence
International Journal of Computer Vision
Region-based tracking using affine motion models in long image sequences
CVGIP: Image Understanding
ACM Computing Surveys (CSUR)
Spatio-Temporal Robust Motion Estimation and Segmentation
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
An unsupervised texture segmentation algorithm with feature space reduction and knowledge feedback
IEEE Transactions on Image Processing
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We present a video segmentation algorithm that accurately finds object boundaries, and does not require any user assistance. After filtering the input video, markers are selected. Around each marker, a volume is grown by evaluating the local color and texture features. The grown volumes are refined and motion trajectories are extracted. Self-descriptors for each volume, mutual-descriptors for a pair of volumes are computed from trajectories. These descriptors designed to capture motion, shape as well as spatial characteristics of volumes. In the fine-to-coarse clustering stage, volumes are merged into objects by evaluating their descriptors. Clustering is carried out until the motion similarity of merged objects at that iteration becomes small. A multi-resolution object tree that gives the video object planes for every possible number of objects is generated. Test results prove the effectiveness of the algorithm.