Portal de Periódicos da CAPES

Revisiting SIRET Video Retrieval Tool

2018; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-319-73600-6_44

1611-3349

Jakub Lokoč, Gregor Kovalčík, Tomáš Soućek,

Multimodal Machine Learning Applications

The known-item and ad-hoc video search tasks still represent challenging problems for the video retrieval community. During last years, the Video Browser Showdown identified several promising approaches that can improve the effectiveness of interactive video retrieval tools focusing on the tasks. We present a major revision of the SIRET interactive video retrieval tool that follows these findings. The new version employs three different query initialization approaches and provides several result visualization methods for effective navigation and browsing in sets of ranked keyframes.