Local feature-based photo album compression by eliminating redundancy of human partition

Chia Hsin Chan*, Bo Hsyuan Chen, W. J. Tsai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2016 Workshops - ACCV 2016 International Workshops, Revised Selected Papers
EditorsJiwen Lu, Kai-Kuang Ma, Chu-Song Chen
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319544069
StatePublished - 1 Jan 2017
Event13th Asian Conference on Computer Vision, ACCV 2016 - Taipei, Taiwan
Duration: 20 Nov 201624 Nov 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10116 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th Asian Conference on Computer Vision, ACCV 2016
City Taipei


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