Simplified Real-time Categorized Vehicle Counting and Speed Estimation

This paper presents a traffic monitoring system that counts, categorizes, and measures the speed of vehicles seen by a stationary camera. Designed to run on low-power hardware, reductions and optimizations on existing algorithms were implemented. The system achieved 3.7 fps using only five watts of power and a count within 10% of the true value with a detector having 95% recall and 95% precision.

Authors

Institutions

Publication Details

Published
2024-08-19
DOI
https://doi.org/10.1109/isocc62682.2024.10762299
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simplified Real-time Categorized Vehicle Counting and Speed Estimation

Percival Magpantay, Ian Christian B. Fernandez, John Richard E. Hizon, Marc Rosales
Traffic Prediction and Management Techniques
article

Simplified Real-time Categorized Vehicle Counting and Speed Estimation

Percival Magpantay, Ian Christian B. Fernandez, John Richard E. Hizon, Marc Rosales
article en

Abstract

This paper presents a traffic monitoring system that counts, categorizes, and measures the speed of vehicles seen by a stationary camera. Designed to run on low-power hardware, reductions and optimizations on existing algorithms were implemented. The system achieved 3.7 fps using only five watts of power and a count within 10% of the true value with a detector having 95% recall and 95% precision.

University of the Philippines Diliman (PH)
Openalex Percentile: Top 77%
Traffic Prediction and Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.