Photo Stream Alignment and Summarization for Collaborative Photo Collection and Sharing

With the popularity of digital cameras and camera phones, it is common for different people, who may or may not know each other, to attend the same event and take pictures and videos from different spatial or personal perspectives. Within the realm of social media, it is desirable to enable these pe...

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Vydáno v:	IEEE transactions on multimedia Ročník 14; číslo 6; s. 1642 - 1651
Hlavní autoři:	Jianchao Yang, Jiebo Luo, Jie Yu, Huang, T. S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.12.2012 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Alignment Applied sciences Artificial intelligence Cameras Computer applications Computer science; control theory; systems Computer systems and distributed systems. User interface Detection, estimation, filtering, equalization, prediction distance learning Exact sciences and technology Facebook feature extraction General aspects image analysis image representation Information, signal and communications theory Kernel Media Occupational training. Personnel. Work management Pictures Redundant Representations Robustness Signal and communications theory Signal, noise Similarity Social networks Software Speech and sound recognition and synthesis. Linguistics Streams Studies Telecommunications and information theory Videos Visualization Sparse graph Similarity Image processing Video signal Remote teaching Alignment feature extraction Linguistics Selection criterion Sparse representation Bipartite graph Pattern extraction Redundancy Abstract Social network Graph theory Pattern recognition Digital photography Drop distance learning Image analysis Social interaction Computer applications image representation Greedy algorithm Metric Integrity
ISSN:	1520-9210, 1941-0077
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Popis
Shrnutí:	With the popularity of digital cameras and camera phones, it is common for different people, who may or may not know each other, to attend the same event and take pictures and videos from different spatial or personal perspectives. Within the realm of social media, it is desirable to enable these people to select and share their pictures and videos in order to enrich memories and facilitate social networking. However, it is cumbersome to manually manage these photos from different cameras, of which the clocks settings are often not calibrated. In this paper, we propose automatic algorithms to address the above problems. First, we accurately align different photo streams or sequences from different photographers for the same event in chronological order on a common timeline, while respecting the time constraints within each photo stream. Given the preferred similarity measures (e.g., visual, and spatial similarities), our algorithm performs photo stream alignment via matching on a bipartite kernel sparse representation graph that forces the data connections to be sparse in an explicit fashion. Furthermore, we can produce a summary master stream from the aligned super stream of photos for efficient sharing by removing those redundant photos in the super stream while accounting for the temporal integrity. Based on a similar kernel sparse representation graph, our master stream summarization algorithm performs greedy backward selection to drop redundant photos without affecting the integrity of remaining photos for the entire event. We evaluate our algorithms on real-world personal online albums for 36 events and demonstrate its efficacy in automatically facilitating collaborative photo collection and sharing.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
ISSN:	1520-9210 1941-0077
DOI:	10.1109/TMM.2012.2198458