@inproceedings{870e1c1dc4f44758a6ee343d1350afa9,
title = "Offline automatic actor tracking in a movie",
abstract = "Automatic extraction and tracking of actors in a movie presents a novel and challenging issue in the field of image and video processing. This paper presents a system that can efficiently track each actor in a movie and extract the scenes that feature a specific actor. The method's facial detection and recognition are based on Haar-like features and Eigenface for SVM, while the actor tracking proposes a novel approach using a B-A-P frame structure. We also modified the Camshift method to enhance tracking performance. Experimental results show that the proposed system can accurately detect and track actors and efficiently solve for the problem of object occlusion.",
keywords = "Object tracking, face detection, face recognition, scene change detection",
author = "Lin, {Chih Yang} and Xie, {Hong Xia} and Wang, {Shang Ming} and Su, {Pin Ming} and Chang, {Wen Thong}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Image and Vision Computing New Zealand, IVCNZ 2017 ; Conference date: 04-12-2017 Through 06-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/IVCNZ.2017.8402496",
language = "???core.languages.en_GB???",
series = "International Conference Image and Vision Computing New Zealand",
publisher = "IEEE Computer Society",
pages = "1--5",
booktitle = "2017 International Conference on Image and Vision Computing New Zealand, IVCNZ 2017",
}