我对 MATLAB 相当陌生，但在过去的几天里熟悉了 Simulink 和计算机视觉。我的问题陈述涉及获取交通/高速公路视频输入并检测是否发生事故。
我计划通过提取质心的值来绘制轨迹、速度差（帧之间）和两辆车之间的距离来做到这一点。我可以成功地跟踪质心，并旨在导出其余的特征。
我不知道如何将这些映射到 ANN。我的意思是，每张图像都有不止一个车辆斑点，这意味着在单个帧/图像中有多个质心。那么，NN 如何同时作用于多个输入（每辆车提取的特征）？我显然错过了链接。请帮我弄清楚。
另外，我在看时间序列数据吗？
I am not exactly sure about your question. The problem can be both time series data and not. You might be able to transform the time series version of the problem, such that it can be solved using ANN, but it is sort of a Maslow's hammer :). Also, Could you rephrase the problem.
As you said, you could give it features from two or three frames and then use the classifier to detect accident or not, but it might be difficult to train such a classifier. The problem is really difficult and the so you might need tons of training samples to get it right, esp really good negative samples (for examples cars travelling close to each other) etc.
There are multiple ways you can try to solve this problem of accident detection. For example : Build a classifier (ANN/SVM etc) to detect accidents without time series data. In which case your input would be accident images and non accident images or some sort of positive and negative samples for training and later images for test. In this specific case, you are not looking at the time series data. But here you might need lots of features to detect the same (this in some sense a single frame version of the problem).
The second method would be to use time series data, in which case you will have to detect the features, track the features (say using Lucas Kanade/Horn and Schunck) and then use the information about velocity and centroid to detect the accident. You might even be able to formulate it for HMMs.