Abstract
This paper presents a passengers counting system based on computer vision. System prototype were created and installed in Kaunas public city transport. Four algorithms were created to calculate passengers on public transport and their advantages and disadvantages were analyzed. Qualitative detection algorithms analysis carried out. Promising results were obtained with the Algorithm of barrier simulation for zones (ABSZ) which has low false rate and it is effective for people-counting. Counting results information can be used for public transport optimization or service quality improvement. DOI: http://dx.doi.org/10.5755/j01.eee.19.3.1232
Highlights
Nowadays computer vision is implemented throughout entire world ranging from security solutions [1] and ending with passenger counting in public transport
Number of reports made in recent years showed that the popularity of video based automatic passengers counting systems (APCS) is increasing [2]–[4]
All methods were tested with a real–life video material witch was collected from a prototype installation in one of the Kaunas public transport buses
Summary
Nowadays computer vision is implemented throughout entire world ranging from security solutions [1] and ending with passenger counting in public transport. Passenger counting is a relevant problem for today’s public transport in the whole world. Knowing the flow of passengers, the public transport companies are able to rationally use their resources, improve service quality and lower the cost of transport [5]. A rational schedule of transport based on the passenger flow allows companies to avoid “empty routes” and to reduce environmental pollution. Bus passengers differ in their look, physical dimensions and outfit. The process is complicated because a person getting in a bus covers from 20 to 50 percent of the image; and in some situations (when two or more people are getting in a bus) people compose up to 90% of the image, and a moment of getting in a bus is very short, from 1 to 5 seconds (2s average). Authors have suggested and investigated four methods for tracking bus passengers, capable of acceptable recognition accuracy for practical applications, while maintaining a low cost of the system hardware – about 2000 Lt for a bus
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