Multi-modal, Multi-labeled Sport Highlight Extraction
| Autor: | HE, JIABIN, 何嘉斌 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 The development of technology makes the generation and dissemination of multimedia more convenient and fast, and the video on the Internet is also growing with each passing day. How to effectively search for the video we need in a huge video resource and quickly gain the content we need in a lengthy video are important research directions of computer vision and video understanding. Basketball is a widely loved sport, so the video about basketball games is too numerous to enumerate. We want to recognize the highlights in the basketball game video, then viewers can save a lot of time watching videos, while enjoy the same pleasure. The video of basketball game contains a variety of information such as images, audios, scores and game time, etc. Different algorithms have been developed to analysis different modals data. However, we hope to combine multi-modal characteristics then using more comprehensive and rich information to recognize the basketball highlights. We explore the different fusion strategies, latent features fusion and early features fusion. In addition, we also train multi-label model based on the factors that affect the highlights to extract the joint features of these factors, and add them to the multi-modal model to further improve the model performance. We call this method multi-modal multi-label based classification. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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