基于ViBe算法运动特征的关键帧提取算法

doi:10.6040/j.issn.1672-3961.0.2019.276

Abstract

Abstract:

Aiming at the fact that the background was dominant in the key frame extraction algorithm, in which the foreground target was too small and it was not easy to extract the features of moving targets in sports video, a key frame extraction algorithm for foreground moving target feature extraction based on background modeling algorithm was proposed, which was called visual background extractor (ViBe) algoritm. The foreground target detection of video sequence was firstly carried out using ViBe algorithm, afterwards the scale-invariant feature transformation (SIFT) features of the foreground moving target were extracted. Based on the similarity calculated from video frame series, the key frames of video were output according to the key frame discrimination method. The experimental results showed that the proposed algorithm could solve the problem of missed selection and misselection in traditional key frame extraction. Compared with the algorithm based on SIFT distribution histogram, the F₁ score was well improved. The algorithm based on ViBe could effectively identify key frames in sports video.

Key words: key frame extraction, background modeling, scale invariant feature transform, target characteristic, feature point matching

CLC Number:

TP37

Qiuling LI,Baomin SHAO,Lei ZHAO,Zhen WANG,Xue JIANG. Key frame extraction based on ViBe algorithm for motion feature extraction[J].Journal of Shandong University(Engineering Science), 2020, 50(1): 8-13.

Figures/Tables 12

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References 20

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视频名称	总帧数/帧	镜头数/个	时长/s
体操视频	7 594	55	303.76
足球视频	5 124	17	204.96
羽毛球视频	3 750	19	50.00
篮球视频	4 432	19	177.28
击剑视频	2 762	24	110.48

方法	体操			足球			羽毛球			篮球			击剑
方法	漏选	错选	选对	漏选	错选	选对	漏选	错选	选对	漏选	错选	选对	漏选	错选	选对
C	43	37	184	10	8	50	13	9	42	18	15	68	20	14	58
D	50	41	177	13	9	47	14	10	41	20	18	66	23	20	55

Key frame extraction based on ViBe algorithm for motion feature extraction

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