Stephens, Kyle and Bors, Adrian Gheorghe orcid.org/0000-0001-7838-0021 (2017) Recognizing Interactions Between People from Video Sequences. In: International Conference on Analysis and Image Analysis (CAIP). Lecture Notes in Computer Science . Springer , pp. 80-91.
Abstract
his research study proposes a new approach to group activ- ity recognition which is fully automatic. The approach adopted is hierar- chical, starting with tracking and modelling local movement leading to the segmentation of moving regions. Interactions between moving regions are modelled using Kullback-Leibler (KL) divergence. Then the statistics of such movement interactions or as relative positions of moving regions is represented using kernel density estimation (KDE). The dynamics of such movement interactions and relative locations is modelled as well in a development of the approach. Eventually, the KDE representations are subsampled and considered as inputs of a support vector machines (SVM) classifier. The proposed approach does not require any interven- tion by an operator
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 21 Feb 2018 09:40 |
Last Modified: | 16 Oct 2024 10:57 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:127776 |
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Filename: CAIP2017_HumAct.pdf
Description: Recognizing Interactions Between People from Video Sequences