Abnormal event detection in nature settings

作者：Liu Yang^*; Li Yibo; Ji Xiaofei

来源：International Journal of Signal Processing, Image Processing and Pattern Recognition, 2014, 7(4): 115-126.

DOI：10.14257/ijsip.2014.7.4.11

• Abnormal event detections
• Descriptors
• Dynamic textures
• Sparse coding
• Spatio-temporal
• State-of-the-art methods
• Testing data
• Unsupervised method

Abnormal event detection in nature settings is an active issue in computer vision domain. A novel unsupervised method is proposed to detect abnormal events by combining dynamic texture and sparse coding. In this method, dynamic texture is used as descriptors in a spatio-temporal manner to describe spatio-temporal volumes of events in videos. Sparse coding is utilized for reconstructing the testing data to measure its normalness. Experiments are conducted on the well known UCSD dataset and UMN dataset to demonstrate the efficiency of the proposed method. The results show that the proposed method outperforms the current state-of-the-art methods.

• 出版日期2014
• 单位南京航空航天大学