A Rotation Invariant Descriptor for Robust Video Copy Detection

Jiang, Shuqiang; Su, Li; Huang, Qingming; Cui, Peng; Wu, Zhipeng

doi:10.1007/978-1-4614-3501-3_46

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…Jiang et al [9] abandoned gradient orientation histograms of the original HOG, but created histograms of quantized gradient intensity, to achieve flip and rotation invariance. Liu et al [10] applied Fourier analysis in polar/spherical coordinates and produced rotation-invariant HOG descriptors.…”

Section: Related Workmentioning

confidence: 99%

Mirror reflection invariant HOG descriptors for object detection

Kanezaki

Mukuta

Harada

2014

2014 IEEE International Conference on Image Processing (ICIP)

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Histogram of Oriented Gradients (HOG) [1] descriptors have been widely used for object detection. An important limitation is that these descriptors tend to vary considerably when objects are horizontally flipped, as is often the case. We propose novel MI-HOG descriptors that are obtained by transforming HOG descriptors to be invariant to mirror reflection. In their extraction process, we consider not only the transform of independent elements but also the combination of those in different location and in orientation, which yields better performance. We showed a greater than 10 % increase in average precision compared to HOG descriptors.

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Section: Related Workmentioning

confidence: 99%

Mirror reflection invariant HOG descriptors for object detection

Kanezaki

Mukuta

Harada

2014

2014 IEEE International Conference on Image Processing (ICIP)

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“…Other works have improved the robustness to a number of distortions, e.g. zoom, rotations [8]. Shang exploits ordinals relations [9].…”

Section: A Robustness and Discriminancementioning

confidence: 99%

A large-scale audio and video fingerprints-generated database of TV repeated contents

Chenot

Daigneault

2014

2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)

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Using specifically-designed lightweight audio and video fingerprints, we were able to detect repeated contents over a quasi-uninterrupted recording of 10+ TV channels, over more than 4 years, starting January 2010 (380,000 hours); the detection independently uses audio and video fingerprints. The results are stored into a database that holds more than 20 million detected repeats. Detections range from a few seconds up to one hour. The database can be explored using a standard web browser. There are many potential applications, e.g. for structuring and documenting contents.

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Weber Binarized Statistical Image Features (WBSIF) based video copy detection

Boukhari

Serir

2016

Journal of Visual Communication and Image Representation

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A Rotation Invariant Descriptor for Robust Video Copy Detection

Cited by 6 publications

References 8 publications

Mirror reflection invariant HOG descriptors for object detection

Mirror reflection invariant HOG descriptors for object detection

A large-scale audio and video fingerprints-generated database of TV repeated contents

Weber Binarized Statistical Image Features (WBSIF) based video copy detection

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