Have you ever pondered the number of vehicles present in a traffic scenario? Have you ever considered the volume of cars navigating through dense traffic? Have you ever contemplated the impact of such traffic on the surrounding routes? We’ve shared these same curiosities and realized the potential to analyze them using computer vision algorithms. We utilized a series of time-lapse images using the coco dataset capturing traffic over a duration and applied an object detection algorithm using YOLO: Real-Time Object Detection to determine the count of vehicles passing within that timeframe.
We conducted an analysis on a collection of time-lapse traffic images using object detection algorithms capable of identifying various vehicle types. Utilizing this data, we calculated the total count of vehicles that traversed through the area and plotted a graph based on the data we collected from running this object model.
The graph was plotted with the number of vehicles on the x-axis against the time taken on the y-axis.The depicted graph illustrates the quantity of vehicles captured by the camera within specific time intervals, condensed from hours to mere seconds. Analyzing this graph reveals a substantial and progressively increasing volume of vehicles at each time interval.
It’s quite remarkable to observe how traffic gradually accumulates over time. Once it initiates at a certain point, it persists until there are no more vehicles present. The buildup of traffic is relentless, ceasing only when either all vehicles have cleared or only a few remain. What’s even more intriguing is our ability to analyze this phenomenon using solely an object detection model.
Numerous occurrences lend themselves to analysis through the application of an object detection model. For instance, we could employ it to scrutinize events like a total solar eclipse, assessing the percentage of the sun obscured during specific time intervals. However, implementation was not feasible as the model lacked training for astronomical events or the analysis of celestial bodies, including those in distant space.
This blog was created by Parithosh Dharmapalan and Pooja Srinivasan.