By the same authors

Recognizing Interactions Between People from Video Sequences

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Department/unit(s)

Publication details

Title of host publicationInternational Conference on Analysis and Image Analysis (CAIP)
DatePublished - Sep 2017
Pages80-91
Number of pages12
PublisherSpringer
VolumeLNCS 10424
Original languageEnglish

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

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

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