一种改进的路口背景频度估计算法

从路口视频图像中实时地构建道路背景图像是基于背景减法的车流量检测的前提。由于路口车流信息复杂,图像受外界环境因素影响大,现有的背景估计算法都有不足之处。该文提出了一种改进的频度背景估计算法,通过离散样本图像,实时地构建背景。该方法不仅算法简单、实时性高,而且增强了在背景估计时对光线变化的适应性,提高了背景建模的准确度,可适用于基于视频的路口信号灯的智能控制系统。

Multimodal background model with noise and shadow suppression for moving object detection

A statistical multimodal background model was described for moving object detection in video surveillance. The solution to some of the problems such as illumination changes, initialization of model with moving objects, and shadows suppression was provided. The background samples were chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation was used to estimate the probability density function of background intensity. Pixel's neighbor information was considered to remove noise due to camera jitter and small motion in the scene. The hue-max-min-diff color information was used to detect and suppress moving cast shadows. The effectiveness of the proposed method in the foreground segmentation was demonstrated in the traffic surveillance application.

Video Scene Invariant Crowd Density Estimation Using Geographic Information Systems

Crowd density is an important factor of crowd stability.Previous crowd density estimation methods are highly dependent on the specific video scene.This paper presented a video scene invariant crowd density estimation method using Geographic Information Systems(GIS) to monitor crowd size for large areas.The proposed method mapped crowd images to GIS.Then we can estimate crowd density for each camera in GIS using an estimation model obtained by one camera.Test results show that one model obtained by one camera in GIS can be adaptively applied to other cameras in outdoor video scenes.A real-time monitoring system for crowd size in large areas based on scene invariant model has been successfully used in 'Jiangsu Qinhuai Lantern Festival,2012'.It can provide early warning information and scientific basis for safety and security decision making.

Research on underwater acoustic channel estimation and temperature factors based on FBMC

The complexity of underwater environment poses a challenge to underwater acoustic communication.In marine environment,different temperatures,depths and salinities would affect the performance of acoustic communication.The analysis of the underwater acoustic channel under the influence of temperature factors provides a reference for further study of the underwater acoustic channel estimation problem based on filter bank multi-carrier(FBMC).The FBMC based offset quadrature amplitude modulation(OQAM)technology(FBMC/OQAM)was introduced into the underwater acoustic communication.Based on FBMC,the underwater acoustic channel estimation technology was studied.By changing the pilot structure to adapt to the complex and variable underwater acoustic channel,the iterative method was used to obtain the channel information with higher accuracy and further improve the performance of channel estimation.Theoretical analysis and simulation results show that iterative channel estimation algorithm based on the new interference approximation method(IAM)pilot proposed in this paper has better performance in underwater acoustic channel.

Video-Based Crowd Density Estimation and Prediction System for Wide-Area Surveillance

Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In this paper, we propose a video-based crowd density analysis and prediction system for wide-area surveillance applications. In monocular image sequences, the Accumulated Mosaic Image Difference (AMID) method is applied to extract crowd areas having irregular motion. The specific number of persons and velocity of a crowd can be adequately estimated by our system from the density of crowded areas. Using a multi-camera network, we can obtain predictions of a crowd's density several minutes in advance. The system has been used in real applications, and numerous experiments conducted in real scenes (station, park, plaza) demonstrate the effectiveness and robustness of the proposed method.

Signal Separation and Instantaneous Frequency Estimation Based on Multi-scale Chirplet Sparse Signal Decomposition

An approach based on multi-scale ehirplet sparse signal decomposition is proposed to separate the malti-component polynomial phase signals, and estimate their instantaneous frequencies. In this paper, we have generated a family of multi-scale chirplet functions which provide good local correlations of chirps over shorter time interval. At every decomposition stage, we build the so-called family of chirplets and our idea is to use a structured algorithm which exploits information in the family to chain chirplets together adaptively as to form the polyncmial phase signal component whose correlation with the current residue signal is largest. Simultaueously, the polynomial instantaneous frequency is estimated by connecting the linear frequency of the chirplet functions adopted in the current separation. Simulation experiment demonstrated that this method can separate the camponents of the multi-component polynamial phase signals effectively even in the low signal-to-noise ratio condition, and estimate its instantaneous frequency accurately.

Vibration Characteristics of Detached Houses in Japan by Onethird Octave Band Frequency to Environmental Vibration Estimation

In recent years, the complaints against the vibration as environmental pollution tends to increase gradually in Japan. The measurement investigation to demonstrate the actual situation of the environmental vibration was carried out for several years. The measurement manual for each vibration source such as operations of factory machine, construction works, road traffics and railways to unify measurement methods was made at the start. From the measurement investigation, the vibration amplification characteristics of the detached house by one-third octave frequency in Japan was analyzed as a purpose to improve estimated precision of the vibration in a detached house. In this paper, the vibration amplification characteristic expressed at onethird octave band frequency was shown, and the characteristics was arranged about a result measured with 27 detached houses in Japan.

A complexity-scalable software-based MPEG-2 video encoder

With the development of general-purpose processors (GPP) and video signal processing algorithms, it is possible to implement a software-based real-time video encoder on GPP, and its low cost and easy upgrade attract developers' interests to transfer video encoding from specialized hardware to more flexible software. In this paper, the encoding structure is set up first to support complexity scalability; then a lot of high performance algorithms are used on the key time-consuming modules in coding process; finally, at programming level, processor characteristics are considered to improve data access efficiency and processing parallelism. Other programming methods such as lookup table are adopted to reduce the computational complexity. Simulation results showed that these ideas could not only improve the global performance of video coding, but also provide great flexibility in complexity regulation.