麻省理工学院计算机科学科研
Computer Science Research at Massachusetts Institute of Technology
一、学校简介
麻省理工学院（Massachusetts Institute of Technology, MIT），创立于1861 年，坐落于美国马萨诸塞州剑桥市（大波士顿地区），是世界著名私立研究型大学。作为世界顶尖高校，麻省理工学院（MIT）尤其以自然及工程学享誉世界，位列 2015-16 年世界大学学术排名（ARWU）工程学世界第 1、计算机科学第 2，与斯坦福大学、加州大学伯克利分校一同被称为工程科技界的学术领袖。截止 2016 年，麻省理工共走出了 19 位图灵奖（计算机界最高奖）得主；先后有87 位诺贝尔奖得主在麻省理工学院工作或学习过。
二、项目简介
科研主题： 麻省理工学院·计算机与人工智能科研导师：MIT 计算机与人工智能专业导师；
科研地点：MIT 计算机与人工智能实验室；
科研时间：寒暑假，每期时间长度为 4 周；具体情况根据学生面试情况由美方进行调整；
报名后 1 周安排面试，面试前辅导学生阅读 1 篇专业论文；
三、招募要求
面向对象：欲申请美国名校计算机或人工智能相关专业的大学生；专业背景：数学、物理、计算机技术、机电一体化等相关专业；软 性背景：有一定的科研履历者优先；
四、科研内容
我们将开发一个三维系统，以可靠的交通监控解决车辆和阴影重叠的问题
The Problem and Goal:
Traffic monitoring systems detect traffic accidents and congestion for immediate assistance and/or traffic flow control. Conventional loop detectors are installed under the pavement and require regular maintenance which is disruptive to traffic. TV-camera based systems are an alternative solution providing non-disruptive monitoring. An advantage of TV-camera-based traffic monitoring systems over loop detectors and acoustic detectors is that the traffic control centers can have a first hand view of the traffic sitution. The problem with conventional TV-camera-based systems is that the systems are confused with overlapping vehicles and shadows, and the systems cannot provide highly accurate measurement results. To avoid overlapping vehicles, overhead structures are used. These structures usually cost more than the machine vision systems.
Our goal is to develop a three-dimensional system for reliable traffic monitoring solving the problem of overlapping vehicles and shadows.
Approach:
Our traffic monitoring system is a TV-camera based system to provide traffic control centers with a real-time view of the traffic situation. We use our three-dimensional vision system described on page 15 to address the accuracy problems with conventional two-dimensional systems. The cameras are located on the side of the road as shown in Figure 1 and expensive overhung structure is unnecessary. The system uses three-dimensional data to eliminate problems with overlapping vehicles and shadows.
The three-camera system produces an edge depth map containing the distances of the edge of objects in the image. The three-dimensional data is used to distinguish between vehicles and enable traffic monitoring. Figure 2 displays the center image and the edge depth map.
The colors indicates the different distances of the object.
Figure 3 is a histogram of the distance vs. number of edges in the depth map. Therefore vehicles are distinguished by the distance from the cameras. Each peak in the histogram correlates to an object in the image.
Current Status and Future Work
Currently the cost-effective real-time three-dimensional vision system is completed and research is being done on distinguishing between overlapping vehicles and shadow elimination. Short term goals consist of vehicle classification, counting and speed measurements. Long term goals involve the development of an automatic incident detection algorithm.
五、科研收获
1、科研履历
2、结识专业高端层次人脉
3、拓展视野
4、理性留学、定位专业和就业
5、提升外语
6、表现优秀的同学将获得导师推荐信
