Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimizatio...
It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subre...
In this paper, we study the feasibility of SIFT features for the tasks of object recognition and tracking within the framework of the IVSEE system design. The IVSEE system is inte...
An online feature evaluation method for visual
object tracking is put forward in this paper. Firstly, a
combined feature set is built using color histogram (HC)
bins and gradien...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...