ENHANCING AUDIENCE EXPERIENCE IN TRADITIONAL THAI LONG-BOAT RACING THROUGH SEMI-AUTOMATED COMPETITION RANKING FOR STREAMING (SACRS)
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Thirachit Saenphon, Punnarust Silparattanawong
ผู้เผยแพร่: ICIC International
ปีที่เผยแพร่ (ค.ศ.): 2026
Volume number: 20
Issue number: 2
หน้าแรก: 131
หน้าสุดท้าย: 138
จำนวนหน้า: 8
นอก: 1881-803X
ภาษา: English-United States (EN-US)
บทคัดย่อ
This study introduces the Semi-Automated Competition Ranking for Streaming (SACRS), a system for detecting and ranking long-boats in a Thai traditional longboat racing competition. This system incorporates computer graphics to stream real-time live video content, originating from authentic race venues. This approach aims to enhance the spectators’ experiences during local sporting events, especially, the annual long-boat races that take place along various rivers in Thailand. This research is also to promote the soft power of the dissemination of Thai cultural heritage to effectively engage international audiences on a global scale. This study was trained and tested with the long-boat image dataset from more than 100 real competitions. The proposed system achieved a precision of 91.31%, recall of 68.70%, and overall accuracy of 64.63% with the challenge tasks of viewing angles and various non-ROI objects. This led the researchers to establish the first digital database of long-boat races in Thailand. This study underscores the significance of leveraging contemporary technological capabilities to preserve and present traditional Thai sports to the wider global community.
คำสำคัญ
Deep Learning, Image processing, Sport, Streaming, Thai long-boat racing






