Semantic event detection using cross-domain knowledge

An event and semantic technology applied in the field of classified digital content recording

Inactive Publication Date: 2012-04-11
MONUMENT PEAK VENTURES LLC
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, there are fundamental problems with semantic event detection as follows: first, practical systems need to be able to handle both digital still images and videos, since both digital still images and videos usually exist in the image corpora of real users; second, practical systems need to accommodate real different

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  • Semantic event detection using cross-domain knowledge
  • Semantic event detection using cross-domain knowledge
  • Semantic event detection using cross-domain knowledge

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Embodiment Construction

[0061]Complex semantic events often arise from the co-existence of basic visual concepts. For example, "wedding" is a semantic event associated with certain schema-formed visual concepts (such as "person", "flower", "park", etc.). Visual concepts are generally defined as pictorial content properties of images, and are often semantically represented by words that are broader than those used to identify specific events. Thus, visual concepts form a subset of image content properties that can contribute to specific events.

[0062] In the present invention, basic visual concepts are first detected from images, and a semantic event detector is built in the concept space instead of the original low-level feature space. The benefits of this approach include at least two aspects. First, visual concepts are higher-level and more intuitive descriptors than original low-level features. As described in "Visual event detection using multi-dimensional concept dynamics" published by IEEE...

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Abstract

A method for facilitating semantic event classification of a group of image records related to an event. The method using an event detector system for providing: extracting a plurality of visual features from each of the image records; wherein the visual features include segmenting an image record into a number of regions, in which the visual features are extracted; generating a plurality of concept scores for each of the image records using the visual features, wherein each concept score corresponds to a visual concept and each concept score is indicative of a probability that the image record includes the visual concept; generating a feature vector corresponding to the event based on the concept scores of the image records; and supplying the feature vector to an event classifier that identifies at least one semantic event classifier that corresponds to the event.

Description

technical field [0001] The present invention relates to classifying digital content records, such as digital still images or video. In particular, the invention relates to the classification of digital content records based on semantic event detection. Background technique [0002] The advent of low-cost consumer electronics imaging technology has resulted in a dramatic increase in the number of digital images captured by the average user. In fact, as various forms of electronic storage have become cheaper over time, users have tended to take more digital still images and video, and to keep digital still images and video that they would have otherwise discarded. As such, the average user faces increasing difficulties in properly identifying and categorizing digital images for storage and later retrieval. Typically, such identification and classification is usually performed manually, which is an extremely time-consuming process for the user. [0003] As just one example, ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F17/30808G06F17/30256G06K9/00711G06K9/00664G06F17/30805G06F17/30802G06F16/5838G06F16/7857G06F16/7854G06F16/785G06V20/10G06V20/40
Inventor A·C·路易W·江
Owner MONUMENT PEAK VENTURES LLC
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