SPEED-ADAPTIVE STREET VIEW IMAGE GENERATION USING DRIVING VIDEO RECORDER

Hua-Tsung Chen, Devi Eddy, Ruei-Lin Chen, Chien Li Chou

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

With the rapid development and reduced cost of digital video capturing devices, driving video recorders (DVRs) begin to gain widespread popularity. What is seen and what happens along the way can thus be recorded in videos. However, searching for a specific scene or event among such massive video collections is laborious and tedious. In this paper, we develop a speed-adaptive street view image generation system using general front-mounted DVRs, requiring no additional devices deployed. Visual summaries of street scenes along the way can be provided, allowing users to retrieve a video clip corresponding to a specific road section quickly. An efficient algorithm for estimating the distance a pixel has moved between two consecutive frames is also proposed, so a street view image can be generated with an appropriate aspect ratio without demanding a constant driving speed. Experiments on an extensive data set show that our proposed system can efficiently generate street view images under different lighting and weather conditions, demonstrating its feasibility.
原文English
主出版物標題IEEE International Conference on Multimedia & Expo (ICME)
DOIs
出版狀態Published - 2016

指紋 深入研究「SPEED-ADAPTIVE STREET VIEW IMAGE GENERATION USING DRIVING VIDEO RECORDER」主題。共同形成了獨特的指紋。

引用此