Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.     

Motion Perception Using Analog VLSI

Motion perception is arguably a fundamental mechanism used by natural species to accomplish a number of tasks, such as navigating freely in an unknown environment. Traditional motion perception methods tend to be computationally intensive, requiring powerful computers and large memories. However, by copying biological mechanisms, such as elementary motion discrimination at the early stages of the visual processing paths, it should be possible to build small and efficient motion perception systems. This paper describes the manner in which a simple motion perception model based on the insect visual system has been implemented using mixed analog/digital VLSI. The device has been fabricated in a 2 micron double metal, double polysilicon process, and comprises 61 photo-detectors, and associated analog and digital circuitry. While not entirely successful in that component mismatches hamper the detection of dark-to-bright changes in contrast, the results clearly show the feasibility of using such a device in autonomous control systems.     

几种新型的光电器件

描述用ＳＯＩ技术制造的光耦合ＭＯＳ继电器和多量子阱长波和红外探测器，以及集成异质结晶体管和激光二管于一体的高增益，高灵敏的光电子开关器件，文中着重介绍这些器件的结构，制造工和器件特性，并对其进行了讨论。     

强度型光纤传感器的信号检测系统

本文阐述了一种可提高强度型光纤传感器测量精度的检测系统。该系统利用同一检测电路交替检测信号、参考通道的输出信号，并将信号、参考两通道的检测结果相除，从而消除了因发光二极管光源波动及检测电路系统不稳定所带来的误差。采用同步相关技术抑制了噪声，提高了输出信噪比。实验证明，当时间常数ＲＣ为０．０５Ｓ时，采用该检测系统可获得优于千分之一的零点稳定性和优于２×１０３的输出信噪比。     

GaAs器件工艺中等离子刻蚀及计算机辅助监控技术研究

用Ｎ２气和ＮＦ３反应气体，在较低的刻蚀功率下实现了用薄正性光刻胶ＡＺ１５１８作掩模，均匀、快速刻蚀ＳｉＯ２，ＳｉＯＮ，Ｓｉ３Ｎ４，ＷＮ，Ｗ等材料的等离子刻蚀技术。利用到蚀过程中射频参数的变化和计算机技术，将射频参数的变化在计算机屏幕上实时显示，实现了计算机辅助监控和终点检测技术。     

应用烃类直接检测技术预测天然气藏

柴达木盆地位于青藏高原北部，是中国大型含油气盆地之一，历经４０年的勘探，发现了丰富的油气资源。柴达木盆地东部地区是第四纪沉降与沉积中心，区内第二系生储气岩厚度大、分布广、第四纪新构造运动形成的同生沉积构造发育、保存完整、具有形成大中型天然气田的地质条件。此外，由于该地区含气地层时代新、埋藏浅、成岩与胶结作用差、含气层厚度大、孔渗性好，加之构造条件简单，人文干扰小、是应用烃直接检测技术寻找天然气的有     

A novel approach to detecting DDoS Attacks at an Early Stage

Distributed Denial-of-Service (DDoS) attacks pose a serious threat to Internet security. Most current research focuses on detection and prevention methods on the victim server or source side. To date, there has been no work on defenses using valuable information from the innocent client whose IP has been used in attacking packets. In this paper, we propose a novel cooperative system for producing warning of a DDoS attack. The system consists of a client detector and a server detector. The client detector is placed on the innocent client side and uses a Bloom filter-based detection scheme to generate accurate detection results yet consumes minimal storage and computational resources. The server detector can actively assist the warning process by sending requests to innocent hosts. Simulation results show that the cooperative technique presented in this paper can yield accurate DDoS alarms at an early stage. We theoretically show the false alarm probability of the detection scheme, which is insensitive to false alarms when using specially designed evaluation functions. This work is partially supported by HK Polyu ICRG A-PF86 and CERG Polyu 5196/04E, and by the National Natural Science Foundation of China under Grant No. 90104005.     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.