most citedVision based Pedestrian Potential Risk Analysis based on Automated Behavior Feature Extraction for Smart and Safe City

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Identifying the exterior image of buildings on a 3D map and extracting elevation information using deep learning and digital image processing

Donghwa Shon, Byeongjoon Noh, Nahyang Byun

Despite the fact that architectural administration information in Korea has been providing high-quality information for a long period of time, the level of utility of the informati…

cs.CV2021

Analyzing vehicle pedestrian interactions combining data cube structure and predictive collision risk estimation model

Byeongjoon Noh, Hansaem Park, Hwasoo Yeo

Traffic accidents are a threat to human lives, particularly pedestrians causing premature deaths. Therefore, it is necessary to devise systems to prevent accidents in advance and r…

cs.CV2021

Automated Object Behavioral Feature Extraction for Potential Risk Analysis based on Video Sensor

Byeongjoon Noh, Dongho Ka, Wonjun Noh +1

Pedestrians are exposed to risk of death or serious injuries on roads, especially unsignalized crosswalks, for a variety of reasons. To date, an extensive variety of studies have r…

cs.CV20211 cited

Vision based Pedestrian Potential Risk Analysis based on Automated Behavior Feature Extraction for Smart and Safe City

Byeongjoon Noh, Dongho Ka, David Lee +1

Despite recent advances in vehicle safety technologies, road traffic accidents still pose a severe threat to human lives and have become a leading cause of premature deaths. In par…

cs.CV2021

A novel method of predictive collision risk area estimation for proactive pedestrian accident prevention system in urban surveillance infrastructure

Byeongjoon Noh, Hwasoo Yeo

Road traffic accidents, especially vehicle pedestrian collisions in crosswalk, globally pose a severe threat to human lives and have become a leading cause of premature deaths. In…