In this paper, we propose a method of object recognition and segmentation using Scale-Invariant Feature Transform (SIFT) and Graph Cuts. SIFT feature is invariant for rotations, s...
This paper presents a robust and efficient skeleton-based graph matching method for object recognition and recovery applications. The novel feature is to unify both object recogni...
Abstract. There is a variety of methods for ranking objectives in multiobjective optimization and some are difficult to define because they require information a priori (e.g. esta...
Background subtraction is commonly used to detect foreground objects in video surveillance. Traditional background subtraction methods are usually based on the assumption that the...
This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...