Camera meta-data for content categorization

• US 20020140843A1
• Filed: 04/03/2001
• Published: 10/03/2002
• Est. Priority Date: 04/03/2001
• Status: Active Grant

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Lin, Oian, Tretter, Daniel R.
• Granted Patent: US 6,977,679 B2
• Time in Patent Office: Days
• US Class Current: 348/362
• CPC Class Codes: G06F 16/55 Clustering; Classification
• CPC Class Codes: G06F 16/58 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

A method and system for categorizing non-textual subject data, such as digital images, content-based data and meta-data to determine outcomes of classification tasks. The meta-data is indicative of the operational conditions of a recording device during the capturing of the content-based data. For example, the non-textual subject data may be a digital image captured by a digital camera, and the meta-data may include automatic gain setting, film speed, shutter speed, aperture/lens index, focusing distance, date and time, and flash/no flash operation. The subject image is tagged with selected classifiers by subjecting the image to a series of classification tasks utilizing both content-based data and meta data to determine classifiers associated with the subject image.

Claims

1. A method for classifying blocks of data comprising the steps of:

capturing a block of non-textual data using a recording device for which settings for data-capture attributes are indicative of characteristics of said non-textual data;

linking meta-data with said block of non-textual data, said meta-data corresponding to at least one said data-capture attribute during said capture by said recording device; and

performing automated processing to assign description to contents of said block, including utilizing said meta-data in determining said description.

2. The method of claim 1 wherein said step of capturing includes recording at least one of an image file by an image-capture device and audio file by an audio recorder.

3. The method of claim 1 wherein said step of linking includes obtaining exposure information that identifies an exposure setting of said recording device.

4. The method of claim 1 wherein said step of capturing further includes configuring said block as a file of non-textual data in a digital format and wherein said step of linking includes forming a tag to said file, said tag being indicative of a plurality of exposure time, automatic gain, film speed, shutter speed, white balance, aperture/lens index, focusing index, and flash/no flash operation.

5. The method of claim 1 further including a step of transmitting said block of said non-textual data and said meta-data from said recording device to a computer for performing said automated processing.

6. The method of claim 1 wherein said automated processing includes analyzing said non-textual data and said meta-data to identify content-based information and manipulating said content-based information to derive said description.

7. The method of claim 6 wherein said step of analyzing includes applying digital signal processing (DSP) to said non-textual data.

8. The method of claim 1 wherein said step of performing said automated processing includes assigning a semantic expression to said block of non-textual data for use as at least one descriptor for one of organizing said blocks of data and matching a query during a search for said block of non-textual data.

9. A system for classifying subject data comprising:

a recording device for capturing non-textual subject data and for recording meta-data, said meta-data being specific to an operational mode of said recording device during capturing of said non-textual subject data; and

a processor configured to implement a classification technique utilizing both of said non-textual subject data and said meta-data for identifying at least one classifier, said classifier being representative of an attribute of said subject data.

10. The system of claim 9 wherein said recording device is a digital camera.

11. The system of claim 9 wherein said operational mode of said recording device is based on a state as determined by at least one of exposure time, auto gain setting, film speed, shutter speed, white balance, aperture/lens index, focusing distance, and flash/no flash operation.

12. The system of claim 9 wherein said classification technique is a sequential progression of decision making comprising a plurality of classification nodes, at least some of said classification nodes including algorithms for determining which of a plurality of alternative next classification nodes is to be encountered in said sequential progression of decision making.

13. The system of claim 9 wherein said classification technique is a neural network having an input stage, an output stage and at least one decision-making stage, said decision-making stage comprising a plurality of classification nodes, at least some of said classification nodes configured to receive a plurality of weighted inputs from other classification nodes within said decision-making stage and from said input stage for generating an output as a basis for identifying classifiers.

15. The method of claim 14 wherein said step of establishing includes a learning procedure in which said content-based data is extracted from each of a plurality of learning images and said meta-data is identified for each said learning image, said meta-data for each said learning image being indicative of operational conditions of said data-capturing device during capture of said learning image.

16. The method of claim 15 further comprising a step of generating a plurality of learning classifiers that are descriptive of said learning images, said step of generating including applying content-based analysis for said content-based data and meta-data analysis for said meta-data.

14. A method of categorizing files of non-textual data comprising the steps of:

establishing an evaluation system for decision making, including using automated processing techniques to define a plurality of algorithms, said algorithms utilizing both of content-based data and meta-data, said content-based data corresponding to content information of a file of said non-textual data and said meta-data corresponding to data-capturing settings of a data-capturing device during capture of said file of non-textual data;

capturing a file of non-textual subject data; and

processing said file of non-textual subject data through said evaluation system for decision making to selectively identify a plurality of classifiers associated with said file of non-textual subject data.