18th International Conference on Pattern Recognition (ICPR'06) 2006
DOI: 10.1109/icpr.2006.360
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Abstract: As part of ITS technology, to achieve quick map updates, we propose a method for automatically detecting changes in streetscapes from images captured by car-mounted omnidirectional cameras. It comprises two stages; accurate alignment of a map and street images taken at various times, and detection of changes in streetscapes from the aligned data. The system will collect data via many free-running cars fitted with low-cost equipment to obtain images at various times and along routes. In the first stage, we proc… Show more

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Cited by 15 publications
(7 citation statements)
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“…They also usually employ supporting sensors to achieve localization-either an IMU [5] or odometry information [14]. A simpler approach is to localize against the closest database image, of known location, using DTW (or Dynamic Programming) to remove temporal differences between input and database image streams [6], [15]. The matching between sample images and those in the database can be performed by using a kind of template matching [15], or by using a low bit-rate image sequence instead of single images [16], which is stable in varying environments but does not provide high localization accuracy.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…They also usually employ supporting sensors to achieve localization-either an IMU [5] or odometry information [14]. A simpler approach is to localize against the closest database image, of known location, using DTW (or Dynamic Programming) to remove temporal differences between input and database image streams [6], [15]. The matching between sample images and those in the database can be performed by using a kind of template matching [15], or by using a low bit-rate image sequence instead of single images [16], which is stable in varying environments but does not provide high localization accuracy.…”
Section: Related Workmentioning
confidence: 99%
“…A simpler approach is to localize against the closest database image, of known location, using DTW (or Dynamic Programming) to remove temporal differences between input and database image streams [6], [15]. The matching between sample images and those in the database can be performed by using a kind of template matching [15], or by using a low bit-rate image sequence instead of single images [16], which is stable in varying environments but does not provide high localization accuracy. Novel feature based methods have also been proposed [7], where the epipole calculated from matched features between images is tracked.…”
Section: Related Workmentioning
confidence: 99%
“…The DTW method is a sequence matching method that could be applied to two sequences with different lengths, and has also been used for video segment matching [2,4,6]. When two video segments X and Y are represented as sequences of feature vectors (x 1, .…”
Section: Related Workmentioning
confidence: 99%
“…피사체 인식 방법은 마크를 사용하는 방법 [16,28], 이미지 데이터베이스에 있는 이미지 들과 비교하는 방법 [8,23], 모델 기반 방법 [22,26], 랜드마크(landmark) 기반의 방법 [20,25] …”
Section: 서 론unclassified