Semiautomatic video object generation using multivalued watershed and partition lattice operators

We conceive the problem of multiple semantic wide object (SVO) extraction as an issue of designing extensive operators on the lattice of partitions. As a result, we propose a framework based on spatial partition generation and application of optimal operators on the generated partitions. The first stage is obtained with a multivalued morphological spatial segmentation method that incorporates an edge-driven marker extraction algorithm and a growing method which integrates both color and edge information. For the second stage, we propose a new spatio-temporal regional maximum likelihood partition operator for extraction purposes. Subjective and objective evaluation of the experimental results obtained with our approach on several MPEG-4 test video sequences show that it accurately tracks multiple SVOs in several scenarios, while improving the SVO extraction precision compared to traditional watershed techniques.