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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Veröffentlicht in:IEEE transactions on multimedia Jg. 14; H. 6; S. 1642 - 1651
Hauptverfasser: Jianchao Yang, Jiebo Luo, Jie Yu, Huang, T. S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.12.2012
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
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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Zusammenfassung: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.
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ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2012.2198458