Scipediacontent: Scipediacontent moved page Draft Content 291228723 to Wang et al 2017b

2021-01-25T09:46:29Z

Scipediacontent moved page Draft Content 291228723 to Wang et al 2017b

Scipediacontent: Created page with " == Abstract == With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion âtexturesâ f..."

2021-01-25T09:46:25Z

Created page with " == Abstract == With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion âtexturesâ f..."

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== Abstract ==

With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion âtexturesâ from dynamic Spatio-Temporal Volume (STV) blocks formulated by live video streams has been proposed. This paper starts from introducing the common approach for STV construction and corresponding Spatio-Temporal Texture (STT) extraction techniques. Next the crowd motion information contained within the random STT slices are evaluated based on the information entropy theory to cull the static background and noises occupying most of the STV spaces. A preprocessing step using Gabor filtering for improving the STT sampling efficiency and motion fidelity has been devised and tested. The technique has been applied on benchmarking video databases for proof-of-concept and performance evaluation. Preliminary results have shown encouraging outcomes and promising potentials for its real-world crowd monitoring and control applications.

== Original document ==

The different versions of the original document can be found in:

* [http://eprints.hud.ac.uk/id/eprint/33565/1/p_17.pdf http://eprints.hud.ac.uk/id/eprint/33565/1/p_17.pdf]

* [http://shura.shu.ac.uk/18879/1/ICAC17-1.pdf http://shura.shu.ac.uk/18879/1/ICAC17-1.pdf]

* [http://xplorestaging.ieee.org/ielx7/8067274/8081956/08082025.pdf?arnumber=8082025 http://xplorestaging.ieee.org/ielx7/8067274/8081956/08082025.pdf?arnumber=8082025],
: [http://dx.doi.org/10.23919/iconac.2017.8082025 http://dx.doi.org/10.23919/iconac.2017.8082025]

* [https://dblp.uni-trier.de/db/conf/iconac/iconac2017.html#HaoXWLF17 https://dblp.uni-trier.de/db/conf/iconac/iconac2017.html#HaoXWLF17],
: [http://eprints.hud.ac.uk/id/eprint/33565 http://eprints.hud.ac.uk/id/eprint/33565],
: [http://shura.shu.ac.uk/id/eprint/18879 http://shura.shu.ac.uk/id/eprint/18879],
: [https://www.scipedia.com/public/Yu_et_al_2017a https://www.scipedia.com/public/Yu_et_al_2017a],
: [https://pure.hud.ac.uk/en/publications/an-effective-video-processing-pipeline-for-crowd-pattern-analysis https://pure.hud.ac.uk/en/publications/an-effective-video-processing-pipeline-for-crowd-pattern-analysis],
: [https://academic.microsoft.com/#/detail/2765509810 https://academic.microsoft.com/#/detail/2765509810]

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Wang et al 2017b - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 291228723 to Wang et al 2017b

Scipediacontent: Created page with " == Abstract == With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion âtexturesâ f..."

Scipediacontent: Created page with " == Abstract == With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion âtexturesâ f..."