TY - GEN
T1 - Pyramid histograms of motion context with application to angiogram video classification
AU - Wang, Fei
AU - Zhang, Yong
AU - Beymer, David
AU - Greenspan, Hayit
AU - Syeda-Mahmood, Tanveer
PY - 2011
Y1 - 2011
N2 - Due to poor image quality as well as the difficulty of modeling the non-rigid heart motion, motion information has rarely been used in the past for angiogram analysis. In this paper we propose a new motion feature for the purpose of classifying angiogram videos according to their viewpoints. Specifically, local motion content of the video around the anatomical structures cardiac vessels is represented using the so-called "motion context", a motion histogram representation in polar coordinates within a local patch. The global motion layout is captured as pyramid histograms of the motion context (PHMC) in a manner similar to that proposed by the Spatial Pyramid Kernel [1]. The PHMC is a robust representation of the motion features in a video sequence. Through experiments on a large database of angiograms obtained from both diseased and control subjects, we show that our technique consistently outperforms state-of-the-art methods in the angiogram classification test.
AB - Due to poor image quality as well as the difficulty of modeling the non-rigid heart motion, motion information has rarely been used in the past for angiogram analysis. In this paper we propose a new motion feature for the purpose of classifying angiogram videos according to their viewpoints. Specifically, local motion content of the video around the anatomical structures cardiac vessels is represented using the so-called "motion context", a motion histogram representation in polar coordinates within a local patch. The global motion layout is captured as pyramid histograms of the motion context (PHMC) in a manner similar to that proposed by the Spatial Pyramid Kernel [1]. The PHMC is a robust representation of the motion features in a video sequence. Through experiments on a large database of angiograms obtained from both diseased and control subjects, we show that our technique consistently outperforms state-of-the-art methods in the angiogram classification test.
UR - http://www.scopus.com/inward/record.url?scp=79957653514&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-642-21028-0_49
DO - https://doi.org/10.1007/978-3-642-21028-0_49
M3 - منشور من مؤتمر
SN - 9783642210273
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 384
EP - 391
BT - Functional Imaging and Modeling of the Heart - 6th International Conference, FIMH 2011, Proceedings
T2 - 6th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2011
Y2 - 25 May 2011 through 27 May 2011
ER -