On-Vehicle Video Localization Technique based on Video Search using Real Data on the Web

Kazuma Fukumoto; Hiroshi Kawasaki; Shintaro Ono; Hiroshi Koyasu; Katsushi Ikeuchi

doi:10.1007/s13177-014-0086-z

On-Vehicle Video Localization Technique based on Video Search using Real Data on the Web

Kazuma Fukumoto, Hiroshi Kawasaki, Shintaro Ono, Hiroshi Koyasu, Katsushi Ikeuchi

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Recently, the mounting of on-vehicle camera is increasing to general cars. Because of this, some users start to upload the on-vehicle videos to web. So that, a number of on-vehicle videos are available nowadays. In this paper, in order to localize car, we propose the efficient matching method for such on-vehicle videos using Temporal Height Image (THI), Affine SIFT and Bag of Feature. THI retains information of relative building height from temporal image sequence. Then we extract robust features from the THI by using Affine SIFT. We realize efficient matching by expressing their features using Bag of features. We conducted experiments to show the efficiency of the proposed method by real image sequences of the city.

Original language	English
Pages (from-to)	63-74
Number of pages	12
Journal	International Journal of Intelligent Transportation Systems Research
Volume	13
Issue number	2
DOIs	https://doi.org/10.1007/s13177-014-0086-z
Publication status	Published - May 1 2015
Externally published	Yes

All Science Journal Classification (ASJC) codes

Software
Control and Systems Engineering
Neuroscience(all)
Information Systems
Automotive Engineering
Aerospace Engineering
Computer Science Applications
Applied Mathematics

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10.1007/s13177-014-0086-z

Cite this

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title = "On-Vehicle Video Localization Technique based on Video Search using Real Data on the Web",

abstract = "Recently, the mounting of on-vehicle camera is increasing to general cars. Because of this, some users start to upload the on-vehicle videos to web. So that, a number of on-vehicle videos are available nowadays. In this paper, in order to localize car, we propose the efficient matching method for such on-vehicle videos using Temporal Height Image (THI), Affine SIFT and Bag of Feature. THI retains information of relative building height from temporal image sequence. Then we extract robust features from the THI by using Affine SIFT. We realize efficient matching by expressing their features using Bag of features. We conducted experiments to show the efficiency of the proposed method by real image sequences of the city.",

author = "Kazuma Fukumoto and Hiroshi Kawasaki and Shintaro Ono and Hiroshi Koyasu and Katsushi Ikeuchi",

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AU - Fukumoto, Kazuma

AU - Kawasaki, Hiroshi

AU - Ono, Shintaro

AU - Koyasu, Hiroshi

AU - Ikeuchi, Katsushi

PY - 2015/5/1

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AB - Recently, the mounting of on-vehicle camera is increasing to general cars. Because of this, some users start to upload the on-vehicle videos to web. So that, a number of on-vehicle videos are available nowadays. In this paper, in order to localize car, we propose the efficient matching method for such on-vehicle videos using Temporal Height Image (THI), Affine SIFT and Bag of Feature. THI retains information of relative building height from temporal image sequence. Then we extract robust features from the THI by using Affine SIFT. We realize efficient matching by expressing their features using Bag of features. We conducted experiments to show the efficiency of the proposed method by real image sequences of the city.

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On-Vehicle Video Localization Technique based on Video Search using Real Data on the Web

Abstract

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