The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
복잡하고 시간에 따라 변하는 자연 패턴을 예측하기 위한 목적으로 이미지 시퀀스를 검색하는 새로운 방법이 제안되었습니다. 이를 위해 우리는 메모리 기반 예측이라는 프레임워크를 소개합니다. 과거에 검색된 시퀀스의 시간적 전개를 기반으로 예측 정보를 제공합니다. 본 논문은 기상 레이더 영상의 레이더 에코 패턴을 대상으로 하며, 기상 예보관이 지역 강수량을 예측할 수 있도록 지원하는 영상 검색 방법을 구현하는 것을 목표로 합니다. 레이더 에코 패턴을 특성화하기 위해 에코 패턴의 모양 기반 표현과 속도 필드가 사용됩니다. 비강성 복합 모션을 포함한 로컬 패턴 특징을 표현하기 위해 시간적 텍스처 특징이 도입되었습니다. 또한, 시퀀스의 시간적 전개는 이미지 특징의 고유공간 경로로 표현되며, 고유공간에서 두 시퀀스 사이의 정규화된 거리는 유사한 시퀀스를 검색하는 데 사용되는 비유사성 측정값으로 제안됩니다. 여러 실험을 통해 제안된 검색 방식의 우수한 성능을 확인하고 이미지 시퀀스의 예측 가능성을 나타냅니다.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
부
Kazuhiro OTSUKA, Tsutomu HORIKOSHI, Haruhiko KOJIMA, Satoshi SUZUKI, "Image Sequence Retrieval for Forecasting Weather Radar Echo Pattern" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 7, pp. 1458-1465, July 2000, doi: .
Abstract: A novel method is proposed to retrieve image sequences with the goal of forecasting complex and time-varying natural patterns. To that end, we introduce a framework called Memory-Based Forecasting; it provides forecast information based on the temporal development of past retrieved sequences. This paper targets the radar echo patterns in weather radar images, and aims to realize an image retrieval method that supports weather forecasters in predicting local precipitation. To characterize the radar echo patterns, an appearance-based representation of the echo pattern, and its velocity field are employed. Temporal texture features are introduced to represent local pattern features including non-rigid complex motion. Furthermore, the temporal development of a sequence is represented as paths in eigenspaces of the image features, and a normalized distance between two sequences in the eigenspace is proposed as a dissimilarity measure that is used in retrieving similar sequences. Several experiments confirm the good performance of the proposed retrieval scheme, and indicate the predictability of the image sequence.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_7_1458/_p
부
@ARTICLE{e83-d_7_1458,
author={Kazuhiro OTSUKA, Tsutomu HORIKOSHI, Haruhiko KOJIMA, Satoshi SUZUKI, },
journal={IEICE TRANSACTIONS on Information},
title={Image Sequence Retrieval for Forecasting Weather Radar Echo Pattern},
year={2000},
volume={E83-D},
number={7},
pages={1458-1465},
abstract={A novel method is proposed to retrieve image sequences with the goal of forecasting complex and time-varying natural patterns. To that end, we introduce a framework called Memory-Based Forecasting; it provides forecast information based on the temporal development of past retrieved sequences. This paper targets the radar echo patterns in weather radar images, and aims to realize an image retrieval method that supports weather forecasters in predicting local precipitation. To characterize the radar echo patterns, an appearance-based representation of the echo pattern, and its velocity field are employed. Temporal texture features are introduced to represent local pattern features including non-rigid complex motion. Furthermore, the temporal development of a sequence is represented as paths in eigenspaces of the image features, and a normalized distance between two sequences in the eigenspace is proposed as a dissimilarity measure that is used in retrieving similar sequences. Several experiments confirm the good performance of the proposed retrieval scheme, and indicate the predictability of the image sequence.},
keywords={},
doi={},
ISSN={},
month={July},}
부
TY - JOUR
TI - Image Sequence Retrieval for Forecasting Weather Radar Echo Pattern
T2 - IEICE TRANSACTIONS on Information
SP - 1458
EP - 1465
AU - Kazuhiro OTSUKA
AU - Tsutomu HORIKOSHI
AU - Haruhiko KOJIMA
AU - Satoshi SUZUKI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2000
AB - A novel method is proposed to retrieve image sequences with the goal of forecasting complex and time-varying natural patterns. To that end, we introduce a framework called Memory-Based Forecasting; it provides forecast information based on the temporal development of past retrieved sequences. This paper targets the radar echo patterns in weather radar images, and aims to realize an image retrieval method that supports weather forecasters in predicting local precipitation. To characterize the radar echo patterns, an appearance-based representation of the echo pattern, and its velocity field are employed. Temporal texture features are introduced to represent local pattern features including non-rigid complex motion. Furthermore, the temporal development of a sequence is represented as paths in eigenspaces of the image features, and a normalized distance between two sequences in the eigenspace is proposed as a dissimilarity measure that is used in retrieving similar sequences. Several experiments confirm the good performance of the proposed retrieval scheme, and indicate the predictability of the image sequence.
ER -