TY - GEN
T1 - Instructive video retrieval for surgical skill coaching using attribute learning
AU - Chen, Lin
AU - Zhang, Qiang
AU - Zhang, Peng
AU - Li, Baoxin
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/4
Y1 - 2015/8/4
N2 - Video-based coaching systems have seen increasing adoption in various applications including dance, sports, and surgery training. Most existing systems are either passive (for data capture only) or barely active (with limited automated feedback to a trainee). In this paper, we present a video-based skill coaching system for simulation-based surgical training by exploring a newly proposed problem of instructive video retrieval. By introducing attribute learning into video for high-level skill understanding, we aim at providing automated feedback and providing an instructive video, to which the trainees can refer for performance improvement. This is achieved by ensuring the feedback is weakness-specific, skill-superior and content-similar. A suite of techniques was integrated to build the coaching system with these features. In particular, algorithms were developed for action segmentation, video attribute learning, and attribute-based video retrieval. Experiments with realistic surgical videos demonstrate the feasibility of the proposed method and suggest areas for further improvement.
AB - Video-based coaching systems have seen increasing adoption in various applications including dance, sports, and surgery training. Most existing systems are either passive (for data capture only) or barely active (with limited automated feedback to a trainee). In this paper, we present a video-based skill coaching system for simulation-based surgical training by exploring a newly proposed problem of instructive video retrieval. By introducing attribute learning into video for high-level skill understanding, we aim at providing automated feedback and providing an instructive video, to which the trainees can refer for performance improvement. This is achieved by ensuring the feedback is weakness-specific, skill-superior and content-similar. A suite of techniques was integrated to build the coaching system with these features. In particular, algorithms were developed for action segmentation, video attribute learning, and attribute-based video retrieval. Experiments with realistic surgical videos demonstrate the feasibility of the proposed method and suggest areas for further improvement.
KW - Attribute Learning
KW - Coaching System
KW - Instructive Video Retrieval
UR - http://www.scopus.com/inward/record.url?scp=84946027691&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946027691&partnerID=8YFLogxK
U2 - 10.1109/ICME.2015.7177389
DO - 10.1109/ICME.2015.7177389
M3 - Conference contribution
AN - SCOPUS:84946027691
T3 - Proceedings - IEEE International Conference on Multimedia and Expo
BT - 2015 IEEE International Conference on Multimedia and Expo, ICME 2015
PB - IEEE Computer Society
T2 - IEEE International Conference on Multimedia and Expo, ICME 2015
Y2 - 29 June 2015 through 3 July 2015
ER -