CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Exploiting Visual-Audio-Textual Characteristics for Automatic TV Commercial Block Detection and Segmentation
Liu, Nan1,2; Zhao, Yao1,2; Zhu, Zhenfeng1,2; Lu, Hanqing3
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
2011-10-01
Volume13Issue:5Pages:961-973
SubtypeArticle
AbstractAutomatic TV commercial block detection (CBD) and commercial block segmentation (CBS) are two key components of a smart commercial digesting system. In this paper, we focus our research on CBD and CBS by the means of collaborative exploitation of visual-audio-textual characteristics embedded in commercials. Rather than utilizing exclusively visual-audio characteristics like most previous works, an abundance of textual characteristics associated with commercials are fully exploited. Additionally, Tri-AdaBoost, an interactive ensemble learning manner, is proposed to form a consolidated semantic fusion across visual, audio, and textual characteristics. In order to segment a detected commercial block into multiple individual commercials, additional informative descriptors including textual characteristics are introduced to boost the robustness in the detection of frame marked with product information (FMPI). Together with the characteristics of audio spectral variation pointer and silent position, FMPI can provide a kind of complementary representation architecture to model the similarity of intra-commercial and the dissimilarity of inter-commercial. Experiments are conducted on a large video dataset from both China central television (CCTV) channels and TRECVID'05, and promising experimental results show the effectiveness of the proposed scheme.
KeywordCommercial Detection Commercial Segmentation Multi-modal Fusion Text Detection Video Analysis
WOS HeadingsScience & Technology ; Technology
WOS KeywordVIDEO ; STREAMS
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000295007300011
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3329
Collection模式识别国家重点实验室_图像与视频分析
Affiliation1.Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China
2.Beijing Key Lab Adv Informat Sci & Network Techno, Beijing 100044, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Liu, Nan,Zhao, Yao,Zhu, Zhenfeng,et al. Exploiting Visual-Audio-Textual Characteristics for Automatic TV Commercial Block Detection and Segmentation[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2011,13(5):961-973.
APA Liu, Nan,Zhao, Yao,Zhu, Zhenfeng,&Lu, Hanqing.(2011).Exploiting Visual-Audio-Textual Characteristics for Automatic TV Commercial Block Detection and Segmentation.IEEE TRANSACTIONS ON MULTIMEDIA,13(5),961-973.
MLA Liu, Nan,et al."Exploiting Visual-Audio-Textual Characteristics for Automatic TV Commercial Block Detection and Segmentation".IEEE TRANSACTIONS ON MULTIMEDIA 13.5(2011):961-973.
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