Speed-adaptive street view image generation using driving video recorder
| Autor: | Hua-Tsung Chen, Devi Eddy, Ruei-Lin Chen, Chien-Li Chou |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Pixel
Event (computing) business.industry Computer science Digital video ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Aspect ratio (image) Image (mathematics) Visualization Set (abstract data type) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Videocassette recorder |
| Zdroj: | ICME |
| DOI: | 10.1109/icme.2016.7552861 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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