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학술지 Exploring the Temporal Cues to Enhance Video Retrieval on Standardized CDVA
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저자
조원, 임근택, 김준수, 윤정일, 최유경
발행일
202204
출처
IEEE Access, v.10, pp.38973-38981
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2022.3165177
협약과제
22HH5900, [전문연구실] 기계를 위한 영상 부호화, 서정일
초록
As the demand for large-scale video analysis increases, video retrieval research is also becoming more active. In 2014, ISO/IEC MPEG began standardizing compact descriptors for video analysis, known as CDVA, and it is now adopted as a standard. However, the standardized CDVA is not easily compared to other methods because the MPEG-CDVA dataset used for performance verification is not disclosed, despite the fact that follow-up studies are underway with multiple versions of the CDVA experimental model. In addition, analyses of modules constituting the CDVA framework are insufficient in previous studies. Therefore, we conduct self-evaluations of CDVA to analyze the impact of each module on the retrieval task. Furthermore, to overcome the obstacles identified through these self-evaluations, we suggest temporal nested invariance pooling, abbreviated as TNIP, which implies temporal robustness realized by improving nested invariance pooling, abbreviated as NIP, one of the features in CDVA. Finally, benchmarks of the existing CDVA and the proposed approach are provided on several public datasets. Through this, we show that the CDVA framework is capable of boosting the retrieval performance if utilizing the proposed approach.
KSP 제안 키워드
Compact Descriptors, Follow-up study, Performance verification, Public Datasets, Retrieval performance, Video retrieval, experimental model, large-scale, video analysis
본 저작물은 크리에이티브 커먼즈 저작자 표시 - 비영리 - 변경금지 (CC BY NC ND) 조건에 따라 이용할 수 있습니다.
저작자 표시 - 비영리 - 변경금지 (CC BY NC ND)