The proliferation of digital cameras and scanners has lead to an explosion of digital images, creating large personal image databases. The organization and retrieval of images and videos is already a problem for the typical consumer. Currently, the length of time spanned by a typical consumer's digital image collection is only a few years. The organization and retrieval problem will continue to grow as the length of time spanned by the average digital image and video collection increases, and automated tools for efficient image indexing and retrieval will be required.
Events in people's lives are one of the most common motivations for capturing digital imagery. Often the central themes of these events are celebrations of various types. Identifying the type of celebration can therefore provide a key piece of semantic information that is highly useful for indexing and retrieving digital imagery.
The development of algorithms for classifying images according to an event type is an area of active research. In U.S. Patent Application 2010/0322524 by Das et al., entitled “Detecting significant events in consumer image collections,” a method for determining if an event associated with a collection of digital images is significant is taught. This method evaluates the number of images captured over a time series to determine if an event is significant. It makes no attempt to determine the nature or type of the event.
In U.S. Patent Application 2010/0245625 by Gallagher et al., entitled “Identifying collection images with special events,” a method for associating digital images with special events is taught. This method utilizes dated journal entries and image capture times as the sources of information for determining images for the special events. This method is unable to determine the type of event from just the pixels in the image.
U.S. Patent Application 2009/0297032 by Loui et al., entitled “Semantic event detection for digital content records” teaches a method for semantic event classification. This method utilizes visual features in the images to semantically classify the images.
In the article “Computational models for object detection and recognition” by Abinav Gupta and Amitabha Mukerjee, it is suggested that “the detection of a birthday cake and candles in scene would be useful in summarization of birthday videos.
In the article “Semantic Event Detection For Consumer Photo And Video Collections” by Jiang et al. (IEEE International Conference on Multimedia and Expo, pp. 313-316 2008), the problem of event detection is described in images where a collection of images is captured at an event, and the task is to categorize the event as one of 21 event categories, including “wedding”, “Christmas”, and “birthday.” General features are determined and used to represent images within the event, and a classifier is applied to the images from the event to make a determination.
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