東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Observation Centric and Central Distance Recovery for Tracking of Sports Athletes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Observation Centric and Central Distance Recovery for Tracking of Sports Athletes./
作者:	Huang, Hsiang-Wei.
面頁冊數:	1 online resource (24 pages)
附註:	Source: Masters Abstracts International, Volume: 84-10.
Contained By:	Masters Abstracts International84-10.
標題:	Electrical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29994733click for full text (PQDT)
ISBN:	9798379409531

Observation Centric and Central Distance Recovery for Tracking of Sports Athletes.
Huang, Hsiang-Wei.

Observation Centric and Central Distance Recovery for Tracking of Sports Athletes. - 1 online resource (24 pages)

Source: Masters Abstracts International, Volume: 84-10.

Thesis (M.El.Eng.)--University of Washington, 2023.

Includes bibliographical references

Multi-Object Tracking on humans has improved rapidly with the development of object detection and re-identification algorithms. However, multi-actor tracking over humans with similar appearance and non-linear movement can still be very challenging even for the state-of-the-art tracking algorithm. Current motion-based tracking algorithms often use Kalman Filter to predict the motion of an object, however, its linear movement assumption can cause failure in tracking when the target is not moving linearly. And for multi-player tracking over the sports field, because the players on the same team are usually wearing the same color of jersey, making re-identification even harder both in the short term and long term in the tracking process. In this work, we proposed a motion-based tracking algorithm and three post-processing pipelines for three sports including basketball, football, and volleyball, we successfully handle the tracking of the non-linear movement of players on the sports fields. Experimental results achieved a HOTA of 73.968 on the testing set of ECCV DeeperAction Challenge SportsMOT Dataset, showing the effectiveness of the proposed framework and its robustness in different sports including basketball, football, and volleyball.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798379409531Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

Central distance recoveryIndex Terms--Genre/Form:

542853
Electronic books.

Observation Centric and Central Distance Recovery for Tracking of Sports Athletes.
LDR:02642nmm a2200397K 4500 001 2355815
005 20230523083440.5
006 m o d
007 cr mn ---uuuuu
008 241011s2023 xx obm 000 0 eng d
020 $a 9798379409531
035 $a (MiAaPQ)AAI29994733
035 $a AAI29994733
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Huang, Hsiang-Wei. $3 3696272
245 1 0 $a Observation Centric and Central Distance Recovery for Tracking of Sports Athletes.
264 0 $c 2023
300 $a 1 online resource (24 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 84-10.
500 $a Advisor: Hwang, Jenq-Neng.
502 $a Thesis (M.El.Eng.)--University of Washington, 2023.
504 $a Includes bibliographical references
520 $a Multi-Object Tracking on humans has improved rapidly with the development of object detection and re-identification algorithms. However, multi-actor tracking over humans with similar appearance and non-linear movement can still be very challenging even for the state-of-the-art tracking algorithm. Current motion-based tracking algorithms often use Kalman Filter to predict the motion of an object, however, its linear movement assumption can cause failure in tracking when the target is not moving linearly. And for multi-player tracking over the sports field, because the players on the same team are usually wearing the same color of jersey, making re-identification even harder both in the short term and long term in the tracking process. In this work, we proposed a motion-based tracking algorithm and three post-processing pipelines for three sports including basketball, football, and volleyball, we successfully handle the tracking of the non-linear movement of players on the sports fields. Experimental results achieved a HOTA of 73.968 on the testing set of ECCV DeeperAction Challenge SportsMOT Dataset, showing the effectiveness of the proposed framework and its robustness in different sports including basketball, football, and volleyball.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 649834
650 4 $a Computer science. $3 523869
650 4 $a Sports management. $3 3423935
653 $a Central distance recovery
653 $a Sports athletes
653 $a Multi-object tracking
653 $a Kalman filter
653 $a Motion-based tracking algorithm
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0544
690 $a 0984
690 $a 0430
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a University of Washington. $b Electrical Engineering. $3 2102369
773 0 $t Masters Abstracts International $g 84-10.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29994733 $z click for full text (PQDT)