TY - CONF

T1 - Selective keyframe summarisation for egocentric videos based on semantic concept search

AU - Yousefi, Paria

AU - Kuncheva, Ludmila

PY - 2018

Y1 - 2018

N2 - Large volumes of egocentric video data are being continually collected every day. While the standard video summarisation approach offers all-purpose summaries, here we propose a method for selective video summarisation. The user can query the video with an unlimited vocabulary of terms. The result is a time-tagged summary of keyframes related to the query concept. Our method uses a pre-trained Convolutional Neural Network (CNN) for the semantic search, and visualises the generated summary as a compass. Two commonly used datasets were chosen for the evaluation: UTEgo egocentric video and EDUB lifelog.

AB - Large volumes of egocentric video data are being continually collected every day. While the standard video summarisation approach offers all-purpose summaries, here we propose a method for selective video summarisation. The user can query the video with an unlimited vocabulary of terms. The result is a time-tagged summary of keyframes related to the query concept. Our method uses a pre-trained Convolutional Neural Network (CNN) for the semantic search, and visualises the generated summary as a compass. Two commonly used datasets were chosen for the evaluation: UTEgo egocentric video and EDUB lifelog.

M3 - Paper

T2 - The International Image Processing Applications and Systems Conference

Y2 - 12 December 2018 through 14 December 2018

ER -