2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance 2010
DOI: 10.1109/avss.2010.64
|View full text |Cite
|
Sign up to set email alerts
|

Multi-Camera Analysis of Soccer Sequences

Abstract: The automatic detection of meaningful phases in a soccer game depends on the accurate localization of players and the ball at each moment. However, the automatic analysis of soccer sequences is a challenging task due to the presence of fast moving multiple objects. For this purpose, we present a multi-camera analysis system that yields the position of the ball and players on a common ground plane. The detection in each camera is based on a code-book algorithm and different features are used to classify the det… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
6
0
1

Year Published

2013
2013
2022
2022

Publication Types

Select...
4
3
2

Relationship

0
9

Authors

Journals

citations
Cited by 12 publications
(7 citation statements)
references
References 13 publications
0
6
0
1
Order By: Relevance
“…Hence, the appearance is based on shirt colors only. Similarly to [54], we use 5 identity groups that we denote as referees, team 1, team 2, goal keeper 1 and goal keeper 2. A sample of the dataset is presented in Fig.…”
Section: Soccer -Issiamentioning
confidence: 99%
“…Hence, the appearance is based on shirt colors only. Similarly to [54], we use 5 identity groups that we denote as referees, team 1, team 2, goal keeper 1 and goal keeper 2. A sample of the dataset is presented in Fig.…”
Section: Soccer -Issiamentioning
confidence: 99%
“…Multiple detections relating to the same object may occur in which case, nonmaximum suppression method is applied [16]. For ball detection, circular Hough transform has been used for ball detection [11], [38]. Especially for the cases of partial or total occlusion of the ball, motion history images, along with Freeman chaincode have been employed [21].…”
Section: Existing Workmentioning
confidence: 99%
“…These criteria include blob size, colour and shape (circularity, eccentricity). Variants of Circle Hough Transform, modified to detect elliptical rather than circular objects, are used to verify if a blob contains the ball (D'Orazio et al, 2002;Poppe et al, 2010;Halbinger and Metzler, 2015). To achieve real-time performance and high detection accuracy, a two-stage approach may be employed (D'Orazio et al, 2002).…”
Section: Related Workmentioning
confidence: 99%