Real time traffic video analytics

Analyse road traffic with real time traffic video analytics in a time-efficient and a power-efficient manner.


Problem statement

The customer introduced themselves with an interesting problem of analyzing CCTV video recordings of traffic videos on roadways. They wanted to leverage the CCTV video recordings and generate insightful analytics about the traffic on residential and commercial properties. The challenge was to generate the results of the video analytics in a time-efficient and power-efficient manner.

Our solution

We developed a Deep Neural Network model to recognise six categories of vehicles namely cars, motorcycles, buses, trucks, bicycles, and pedestrians. We first collected the CCTV footage and generated a customized data set containing 2000 images for each class of vehicle. We then trained a Deep Neural Network to classify each class of a vehicle and localize them on a video frame. Since this was a video processing application, the performance was a key metric in addition to the accuracy of the vehicle finder.

Technology stack

Logo for tensor flow library Logo for OpenCV image processing library

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