整合高階模糊派翠網路和特徵點比對之分鏡自動偵測

Automatic Video Shot Boundary Detection Using a Hybrid Approach of HLFPN and Keypoint Matching

林詩詠(LIM SOO YONG)

指導教授 ： 沈榮麟

國立臺北大學/電機資訊學院/資訊工程學系/碩士(2015年)

摘要

視頻的內容可以帶來許多有用的資訊，分析視頻內容可用於索引、瀏覽和檢索視頻。在這當中分鏡偵測（SBD）是一個最基礎卻重要的步驟。在我們前一篇論文中已經提出了一個能有效針對新聞視頻做出分鏡偵測的方法，本文提出了整合前論文的HLFPN和新的特徵點比對技術來提高分鏡偵測的精準度。首先，利用HLFPN所得出的結果來做判斷，接著再用SURF演算法來移除錯誤和找出漸變鏡頭，此方法可以有效的提高分鏡偵測的精準度並將其應用在不同類型的視頻上。

關鍵字

加速稳健特徵 ； 特徵點比對 ； 高階模糊派翠網路 ； 分鏡偵測 ； 差值直方圖

並列摘要

Shot boundary detection (SBD) is an important and fundamental step in video content analysis such as content-based video indexing, browsing, and retrieval. In this paper, we present a hybrid SBD method by integrating a technique of high-level fuzzy Petri net (HLFPN) and keypoint matching. The HLFPN with histogram difference is executed as a pre-detection. Next, the speeded up robust features (SURF) algorithm that is reliably robust to image affine transformation and illumination variation is used to figure out the possible false shots and gradual transition based on the assumption from HLFPN. The top-down design can effectively lower down the computational complexity of SURF algorithm. The proposed algorithm has increased the precision of SBD and can be applied to different types of videos.

並列關鍵字

Keypoint Matching ； High-Level Fuzzy Petri Net ； Shot Boundary Detection ； SURF ； Histogram Difference

參考文獻

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