@inproceedings{5ec66dbb9a7d43a78da682a5b64a8898,
title = "Local feature-based photo album compression by eliminating redundancy of human partition",
abstract = "With the explosive growth of photo uploading on the web, traditional photo album compression using individual image coding is needed to be improved to save the storage spaces. Recently, an advance technique of photo album compression via video compression is proposed which utilizes the similarity between photos to improve the compression performance. In this paper, we modify the original scheme to improve the compression performance when photos containing human beings. Experiment results show that the proposed method outperforms the state-of-the-art method by at most 12.7% of bit-rate savings for compressing photo albums with humans. Comparing with traditional JPEG compression, the proposed method achieves 70% to 85% of bit-rate savings.",
author = "Chan, {Chia Hsin} and Chen, {Bo Hsyuan} and Tsai, {W. J.}",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-54407-6_10",
language = "English",
isbn = "9783319544069",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "143--158",
editor = "Jiwen Lu and Kai-Kuang Ma and Chu-Song Chen",
booktitle = "Computer Vision - ACCV 2016 Workshops - ACCV 2016 International Workshops, Revised Selected Papers",
address = "德國",
note = "13th Asian Conference on Computer Vision, ACCV 2016 ; Conference date: 20-11-2016 Through 24-11-2016",
}