Adaptive weighted fusion with new spatial and temporal fingerprints for improved video copy detection

Kim, Semin; Choi, Jae Young; Han, Seung-Wan; Ro, Yong Man

doi:10.1016/j.image.2014.05.002

Cited by 20 publications

(7 citation statements)

References 39 publications

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“…The work presented in [28] can be viewed as user-specific adaptive fusion approach. Besides this kind of approaches, other adaptive fusion studies are also made [30][31][32]. For instance, the approach proposed in [32] is a typical test-samplespecific adaptive weighted fusion approach.…”

Section: Introductionmentioning

confidence: 99%

Adaptive weighted fusion: A novel fusion approach for image classification

2015

Neurocomputing

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Section: Introductionmentioning

confidence: 99%

Adaptive weighted fusion: A novel fusion approach for image classification

2015

Neurocomputing

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“…When the pBest and gBest are found, each particle will adjust its flight speed and the new location according to equation (4) and (5 …”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

“…The scheme uses an identical sub-band watermark for the same scene, but different parts in different scenes [4]. Semin Kim, et al, proposed a novel modality fusion method designed for combining spatial and temporal fingerprint information to improve video copy detection performance [5]. Antonio Cedillo-Hrenanderz, et al, proposed a transcoding resilient watermarking scheme based on spatio-temporal HVS and DCT.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Video Watermarking Scheme based on Dual Transform Domains and Holography

Jiang¹,

Li²,

Kim³

2015

IJSIA

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“…Semin Kim [7] proposed adaptive weighted fusion with new spatial and temporal fingerprints for improved video copy detection, it's with good robustness against various attacks, but increasing computational complexity. Uniform Local Binary Pattern is low computational complexity and successfully applied in fingerprint recognition, face recognition and other fields.…”

Section: Introductionmentioning

confidence: 99%

Video Copy Detection based on Uniform Local Binary Pattern

Hou¹,

Wang²,

Liu³

2018

dtcse

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Video copy detection techniques are used to detect copies of video widely, this paper proposed a new algorithm based on spatiotemporal analysis for copy detection and compares detection precision and efficiency with existing algorithms. The descriptor encodes the structure of video key frames by computing uniform Local Binary Pattern with rotation invariance. Besides, Chi-square tests are employed to speed up the matching process. The proposed algorithm can deal with various kinds of video transformations, such as brightness conversion, sharpen, contrast and gray scale, especially for video rotation which is not well addressed in existing algorithms. The results of experiments tested on TRECVID 2015 dataset, experimental results indicate that precision and recall are improved, proposed algorithm is with good robustness and discrimination accuracy, detection performance is improved further.

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Adaptive weighted fusion with new spatial and temporal fingerprints for improved video copy detection

Cited by 20 publications

References 39 publications

Adaptive weighted fusion: A novel fusion approach for image classification

Adaptive weighted fusion: A novel fusion approach for image classification

Adaptive Robust Video Watermarking Scheme based on Dual Transform Domains and Holography

Video Copy Detection based on Uniform Local Binary Pattern

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