SYSTEM FOR SEARCH AND METHOD FOR OPERATING THEREOF

• US 20150117759A1
• Filed: 07/24/2014
• Published: 04/30/2015
• Est. Priority Date: 10/25/2013
• Status: Active Grant

• Current Assignee: Hanwha Vision Company Limited (Hanwha Corporation)
• Original Assignee: Samsung Techwin Corporation (Hanwha Corporation)
• Inventors: PARK, Dong Jun, RYU, Yeon Geol, SHIN, Hak Chul, JUNG, Dong Whan
• Granted Patent: US 9,858,297 B2
• Time in Patent Office: Days
• US Class Current: 382/157
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures

Abstract

Provided are a system for search and a method for operating thereof. The system for search includes: a preliminary data analysis part which extracts a variety of attributes through analysis of images being input, analyzes a trend about a category as information requested by a client with the image analysis result, and stores the trend analysis result as metadata; an index part which stores the image analysis result, and structuralizes, organizes and stores the stored metadata in order to easily search the metadata; and a search part which extracts trend information matching a category input by a client, from the index part and provides the trend information in a predetermined format.

Claims

1. A system for search comprising:

a preliminary data analysis part configured to analyze input images to extract a variety of attributes, analyze a trend about a category of information requested by a client by using the variety of extracted attributes, and store the trend analysis as metadata;

an index part configured to make the metadata searchable by structuralizing and storing the metadata; and

a search part configured to extract trend information matching the category of information requested by the client from the searchable metadata and provide the trend information in a predetermined format.

2. The system of claim 1, wherein the preliminary data analysis part comprises:

an image analysis engine configured to analyze the input images and extract the variety of attributes;

a trend analysis engine configured to analyze the trend about the category of information requested by the client and provide the trend analysis, in response to the attribute information being extracted; and

a first storage unit configured to store the trend analysis as metadata.

3. The system of claim 2, wherein the trend analysis engine comprises:

an occurrence frequency analysis unit configured to analyze, as first trend information, an occurrence frequency of the category in a random time period;

a change analysis unit configured to provide second trend information, by analyzing a change in the first trend information; and

a movement line analysis unit configured to provide, as third trend information, a result of movement line analysis of the category, through detection and tracking of a motion in the category.

4. The system of claim 3, wherein the search part is configured to provide metadata of the first trend information in an output screen format that includes upper categories indicated on one axis and, on another axis, visual graphics representing frequencies of occurrences of lower categories included in each upper category.

5. The system of claim 4, wherein, in response to a random lower category being selected from among the lower categories, detailed information of the selected lower category is displayed.

6. The system of claim 3, wherein the search part is configured to provide metadata of the second trend information, in a heat-map format in which a change in occurrence frequencies with respect to a set time is expressed in visual graphics of a heat distribution form.

7. The system of claim 3, wherein the search part is configured to provide metadata from changing the first trend information to second trend information, in a graph format in which a change in occurrence frequencies with respect to a set time is expressed in visual graphics.

8. The system of claim 3, wherein the movement line analysis unit comprises:

a movement line information generation unit configured to generate movement line information through motion detection and tracking in relation to the category from the input image frames;

a noise removing unit configured to remove noise of the movement line information;

a clustering unit configured to make clusters each of which is formed of similar movement line information items in which noise is removed; and

a grouping unit configured to provide, as the third trend information, a result of grouping similar movement line information items by performing artificial intelligence neural network learning with the clustered movement line information items.

9. The system of claim 8, wherein the search part is configured to provide metadata of the third trend information, which is retrieved from the index part, in an output screen format which is formed with a first area where a movement line in the image is displayed and a second area where the result of grouping similar movement line information items by performing artificial intelligence neural network learning is displayed as a self-organizing map.

10. The system of claim 9, wherein, in response to any one group being selected in the second area, a movement line corresponding to the selected group is displayed in the first area.

11. The system of claim 3, wherein the movement line analysis unit comprises:

a movement line information generation unit configured to generate movement line information through motion detection and tracking in relation to the category from the input image frames;

a noise removing unit configured to remove noise of the movement line information;

a point selection unit configured to select arbitrary points included in the movement line information in which noise is removed;

a clustering unit configured to make clusters each of which is formed of similar movement line information items including the points; and

a movement probability calculation unit configured to calculate a probability of moving from any one clustered point to another clustered point, and provide the probability as the third trend information.

12. The system of claim 11, wherein metadata of the third trend information retrieved from the index part is provided in an output screen format in which the clustered points in the image are displayed and the probability of moving from any one clustered point to another clustered point is shown as an arrow.

13. The system of claim 12, the magnitude of the probability of moving is proportional to a size of the arrow.

14. The system of claim 2, wherein the index part comprises:

a second storage unit configured to store an output of the image analysis engine;

an indexing engine configured to structuralize and organize metadata stored in the first storage unit in order to make the metadata searchable; and

a third storage unit configured to store the searchable metadata from the indexing engine.

16. A method for operating a system for search, the method comprising:

extracting, for preliminary data analysis, a variety of attributes by analyzing input images, analyzing a trend about a category of information requested by a client by using the variety of extracted attributes, and storing the trend analysis as metadata;

indexing the stored metadata by structuralizing and storing the stored metadata in order to make the metadata searchable; and

extracting, from the searchable metadata, trend information matching a category input by a client, and providing the extracted trend information in a predetermined format.

15. The system of claim 16, wherein the index part comprises:

a query engine configured to classify a search word input from the client into a category;

a search engine configured to search the second and third storage units for trend information corresponding to the classified category; and

a browsing engine configured to provide the search result of the trend information by the search engine in a predetermined format.

17. The method of claim 16, wherein extracting of the variety of attributes and the analyzing the trend about the category comprises:

extracting the variety of attributes through analysis of the input images; and

in response to the variety of attributes being extracted, analyzing the trend about the category and providing the trend analysis as trend information.

18. The method of claim 17, wherein analyzing the trend about the category and providing the trend analysis comprises:

analyzing, as first trend information, an occurrence frequency of the category in a random time period;

analyzing, as second trend information, a change in the first trend information; and

providing, as third trend information, a result of movement line analysis of the category, through detection and tracking of a motion in the category.

19. The method of claim 18, wherein the providing of the result of movement line analysis comprises:

generating movement line information through motion detection and tracking in relation to the category from the input images;

removing noise of the movement line information;

making clusters each of which is formed of similar movement line information items in which noise is removed; and

providing, as the third trend information, a result of grouping similar movement line information items by performing artificial intelligence neural network learning with the clustered movement line information items.

20. The method of claim 18, wherein the providing of the result of movement line analysis comprises:

generating movement line information through motion detection and tracking in relation to the category from the input images;

removing noise of the movement line information;

selecting arbitrary points included in the movement line information in which noise is removed;

making clusters each of which is formed of similar movement line information items including the points; and

calculating a probability of moving from any one clustered point to another clustered point, and providing the probability as the third trend information.