Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
VisualRank: Applying PageRank to Large-Scale Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Event Recognition Using Kernel Methods with Multilevel Temporal Alignment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploitation of time constraints for (sub-)event recognition
J-MRE '11 Proceedings of the 2011 joint ACM workshop on Modeling and representing events
Indexing media by personal events
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
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We propose a method of mining most informative features for the event recognition from photo collections. Our goal is to classify different event categories based on the visual content of a group of photos that constitute the event. Such photo groups are typical in a personal photo collection of different events. Visual features are extracted from the images, yet the features from individual images are often noisy and not all of them represent the distinguishing characteristics of an event. We employ the PageRank technique to mine the most informative features from the images that belong to the same event. Subsequently, we classify different event categories using the multiple images of the same event because we argue that they are more informative about the content of an event rather than any single image. We compare our proposed approach with the standard bag of features method (BOF) and observe considerable improvements in recognition accuracy.