Unattended Packages Recognition Based on HMM
With the thorough of studying behavior understanding,the detection and analysis of unattended packages is receiving increasing attention from computer vision researchers,it aims at attempting to detect,track and identify people,and more generally,to understand human behaviors,from image sequences involving humans.With application requirements of intelligent video surveillance,in order to achieve the intelligent unattended packages recognition,implement the HMM(Hidden Markov Models) method in unattended packages recognition,provide a project of unattended packages recognition on HMM,took on the image preprocessing,the training HMM parameters,and identifying from a test sequence,and have been studied in the recognition capability.At the end of this survey,some discussions on future directions in motion analysis are also provided.
This paper addresses the problem of the considerably decreased performance of spread spectrum audio watermarking in the presence of time scale modification attack. An adaptive receiver is described, which can precisely estimate the quantization step needed to overcome the time scale modification attack. The proposed scheme obtains significantly lower bit error rates in the presence of DA/AD conversion and time scalemodification, obtaining smaller bit error rate up to an order of value.