Motion detection plays an important role in intelligent video surveillance. This paper introduces a particular background subtraction technique called ViBe. This technique updates the background model randomly and it has established model with fast, high precision and fast processing speed. ViBe algorithm provides the method of updated background model, but slowly eliminates ghost region. This paper presents an improved ViBe algorithm based on region motion classification. The algorithm considers the difference of the movement directions of feature points in foreground regions on adjacent frame, and defines a criterion function to evaluate the difference so that can quickly eliminate ghost regions. Experimental results show that the proposed algorithm quickly remove the ghost region and improve the detection accuracy.
Cast shadow cause serious problem in the extracting of moving objects because shadow pixels are liable to be
misclassified as foreground. Many methods of cast shadow removal have been proposed and many features are selected
in these methods. But since, moving object (MO) and cast shadow are classified by a single linear classifier. As it is
known, each feature has its strength and weakness and is particularly applicable for handling a certain type of variation.
In this paper, a novel framework for feature selection for cast shadow removal based on AdaBoost is proposed.
Experiments are conducted on many scenes and the results prove the validation of the proposed method.