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Abnormal Crowd Motion Behaviour Detection based on SIFT Flow
Dongping Zhang,Kaihang Xu,Huailiang Peng,Ye Shen 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.1
This paper focuses on the detection of the abnormal motion behaviour recognition of the crowd, and proposes an innovation method which is consist of three steps, i.e. SIFT flow + weighted orientation histogram + Hidden Markov Model(HMM). Analogous to optical flow, which is used to get the motion information of the pixels from two adjacent frames, SIFT flow is of higher precision. Next, we build up a a weighted orientation histogram as a statistical measurement for the SIFT flow features from the first step. Finally, the derived histogram is taken as the input for HMM in preparation for the detection of abnormal crowd motion. Experimental results show that compared to the existing method, our proposed one can detect the abnormal motion behaviour more effectively.
Preparation and characterization of boron films used for boron-lined gaseous neutron detectors
Deng Chao,Wang Qibiao,Wu Yadong,Peng Shuming,Liu Fule,Li Huailiang,Cheng Jianfeng,Tuo Xianguo 한국물리학회 2021 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.79 No.7
Boron-lined gaseous neutron detectors are being widely used in neutron detection to replace 3He proportional counters, and the boron film’s parameters comprise the key factors influencing the performance of such detectors. However, the method of characterizing boron film is relatively simple at present. In this study, boron films stuck to ultrathin glass substrate with different mass proportions of epoxy to natural boron (MPENBs) were prepared. A variety of characterization methods, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, white-light interferometry, and multiple tape tests, were used to test the boron films simultaneously, and the test results are discussed herein. Moreover, neutron imaging was conducted to analyze the uniformity of boron-10 atoms. These characterization results demonstrate that the optimized MPENB formulation is 0.16 with the boron atomic ratio of chemical elements (ARCE) at approximately 68.8% and surface roughness Sa = 1.457 μm and that the structure of boron film is uniform and fluffy, contributing to improving the boron-lined method.
Abnormal Crowd Motion Detection with Hidden Conditional Random Fields Model
Dongping Zhang,Kaihang Xu,Yafei Lu,Chen Pan,Huailiang Peng 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.10
Crowd motion analysis in public places is an important research subject in the monitoring field. This paper proposes an approach for detecting abnormal crowd motion using Hidden Conditional Random Fields Model (HCRF). This approach derives variations of motion patterns from direction distribution of the crowd motion obtained by the optical flow and these variations are encoded with HCRF to allow for the detection of abnormal crowd motion. Modeling the temporal neighborhood relations in a video sequence based on HCRF can incorporate hidden states and label the video depending on long range observations. The experimental results show that this proposed algorithm can achieve better results than HMM and CRF.