A novel coding method IVLAD (Improved Vector of Locally Aggregated Descriptors) based on the fusion of features was proposed in this paper.It obtained good performance in behavior recognition.In order to solve the problem that single feature descriptor cannot express space information well

location information was mapped into feature space and then jointly coded to get the video expression vector.In order to avoid the deficiency of the traditional VLAD methods which only consider the distances of features and clustering centers

the distance between each cluster and its most similar feature was also used in the coding stage.Finally concatenating the video expression vector with itself was proposed to raise the dimension of vectors to further improve the recognition accuracy.Furthermore

the influences of the visual dictionary size

the location dictionary size and the normalization method on the recognition accuracy were studied.The experimental results on two large databases UCF101 and HMDB51 have shown that the proposed method had better performance than the traditional VLAD method.