TY - GEN
T1 - Lifelogging keyframe selection using image quality measurements and physiological excitement features
AU - Ratsamee, Photchara
AU - Mae, Yasushi
AU - Jinda-Apiraksa, Amornched
AU - Machajdik, Jana
AU - Ohara, Kenichi
AU - Kojima, Masaru
AU - Sablatnig, Robert
AU - Arai, Tatsuo
PY - 2013
Y1 - 2013
N2 - Keyframe selection is the process of finding a representative frame in an image sequence. Although mostly known from video processing, keyframe selection faces new challenges in the lifelog domain. To obtain a keyframe that is close to a user-selected frame, we propose a keyframe selection method based on image quality measurements and excitement features. Image quality measurements such as contrast, color variance, sharpness, noise and saliency are used to filter high quality images. However, high quality images are not necessarily keyframes because humans also use emotions in the selection process. In this study, we employ a biosensor to measure the excitement of humans. In previous investigation, keyframe selection using only image quality measurements yielded an acceptance rate of 79.70%. Our proposed method achieves an acceptance rate of 84.45%.
AB - Keyframe selection is the process of finding a representative frame in an image sequence. Although mostly known from video processing, keyframe selection faces new challenges in the lifelog domain. To obtain a keyframe that is close to a user-selected frame, we propose a keyframe selection method based on image quality measurements and excitement features. Image quality measurements such as contrast, color variance, sharpness, noise and saliency are used to filter high quality images. However, high quality images are not necessarily keyframes because humans also use emotions in the selection process. In this study, we employ a biosensor to measure the excitement of humans. In previous investigation, keyframe selection using only image quality measurements yielded an acceptance rate of 79.70%. Our proposed method achieves an acceptance rate of 84.45%.
UR - https://www.scopus.com/pages/publications/84893773135
U2 - 10.1109/IROS.2013.6697110
DO - 10.1109/IROS.2013.6697110
M3 - Conference contribution
AN - SCOPUS:84893773135
SN - 9781467363587
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 5215
EP - 5220
BT - IROS 2013
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
Y2 - 3 November 2013 through 8 November 2013
ER -