Technical Paper
Vision-Based Techniques for Identifying Emergency Vehicles
2019-04-02
2019-01-0889
This paper discusses different computer vision techniques investigated by the authors for identifying Emergency Vehicles (EV). Two independent EV identification frameworks were investigated: (1) A one-stage framework where an object detection algorithm is trained on a custom dataset to detect EVs, (2) A two-stage framework where an object classification algorithm is implemented in series with an object detection pipeline to classify vehicles into EVs and non-EVs. A comparative study is conducted for different multi-spectral feature vectors of the image, against several classification models implemented in framework 2. Additionally, a user-defined feature vector is defined and its performance is compared against the other feature vectors. Classification outputs from each of the frameworks are compared to the ground truth, and results are quantitatively listed to conclude upon the ideal decision rule.