Video storage optimization

• US 8,817,094 B1
• Filed: 02/25/2010
• Issued: 08/26/2014
• Est. Priority Date: 02/25/2010
• Status: Active Grant

• Current Assignee: Target Brands Inc. (Target Corporation)
• Original Assignee: Target Brands Inc. (Target Corporation)
• Inventors: Brown, Robert K., Foster, Robert F., Reasoner, Jason D., DePape, Neal B.
• Primary Examiner(s): MADAMBA, GLENFORD J
• Application Number:
  US12/712,720
• Time in Patent Office: 1,643 Days
• Field of Search: 348/143, 348/159
• US Class Current: 348/143
• CPC Class Codes: G08B 13/19667 Details realated to data compression, encryption or encoding, e.g. resolution modes for reducing data volume to lower transmission bandwidth or memory requirements
• CPC Class Codes: G08B 13/19669 Event triggers storage or change of storage policy
• CPC Class Codes: H04N 7/188 Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position signal generation from motion picture films H04N5/253

Abstract

In an illustrative implementation, a system for video storage optimization analyzes user activity to determine how to optimally store video. In a preferred embodiment, a security system records video from a plurality of security cameras and stores the video at the security system and/or a server system, along with associated metadata. The server system monitors user activity, such as live and recorded video viewing behavior, and queries for videos. The server system collects user video viewing behavior statistics, determines trends, and stores both personnel-specific and enterprise-wide settings. An optimization engine analyzes the video info, personnel-specific settings, enterprise-wide settings, and user statistics to determine a storage factor for a video. The optimization engine then determines if a video meets storage factor thresholds and settings for compression or deletion.

Claims

1. A method of optimizing the storage of enterprise-wide security video, the method comprising:

semi-continuously or continuously capturing security video footage at a plurality of distributed enterprise locations;

storing the video footage as a plurality of video files at a centralized location;

accessing the video files from a plurality of video viewing workstations within the enterprise;

tracking a plurality of viewing attributes, the attributes including the times of access and the identities of the video files accessed;

providing an optimization engine to determine a user-centric storage metric and an enterprise-centric storage metric, wherein the user-centric storage metric is based on the frequency with which a distinct category of users accesses video files of a predetermined age at one or more of the video viewing workstations and wherein the enterprise-centric storage metric is based on viewing behavior of at least a representative sample of users within the enterprise, said optimization engine being configured to automatically determine whether to compress or delete video files based on the user-centric storage metric, the enterprise-centric storage metric and a threshold value while preventing video files from being compressed or deleted prior to an initial review by a user, wherein the threshold value is a period of time in which video is to be compressed or deleted and the viewing behavior includes a period of time that lapses before video is viewed; and

,

automatically modifying the threshold value based on the viewing behavior to prevent video files from being compressed or deleted prior to an initial review of the video files by a user.

2. The method of claim 1, wherein at least some of the video viewing workstations are at the distributed enterprise locations.

3. The method of claim 1, wherein a determination is made to compress the video files by storing them in a reduced resolution format or deleting a predetermined percentage of the frames in each video file.

4. The method of claim 1, further including the steps of:

identifying a subset of video files;

determining for the subset of video files the user-centric storage metric, the enterprise-centric storage metric and the threshold value; and

,

determining whether to compress or delete the subset of video files based on the user-centric storage metric, the enterprise-centric storage metric, and the threshold value.

5. The method of claim 4, wherein the subset of video files reflects security video footage taken at the same location or type of location within the enterprise.

6. The method of claim 1, wherein the user-centric storage metric is based on the position or title of personnel accessing the video files.

7. The method of claim 1, wherein the user-centric storage metric is based on a probability that video files of a predetermined type and age will be accessed.

8. A system for optimizing security video storage, the system comprising:

a distributed array of security video systems at a first plurality of locations within an enterprise;

a primary video storage means for storing video files received from the array of security video systems;

a distributed array of video viewing workstations at a second plurality of locations within the enterprise;

a user activity recorder to track the viewing behavior of users at the video viewing workstations; and

,

an optimization engine to determine a user-centric storage metric and an enterprise-centric storage metric, wherein the user-centric storage metric is based on the frequency with which a distinct category of users accesses video files of a predetermined age at one or more of the video viewing workstations and wherein the enterprise-centric storage metric is based on the viewing behavior of at least a representative sample of users within the enterprise, said optimization engine being configured to automatically determine whether to compress or delete video files based on the user-centric storage metric, the enterprise-centric storage metric and a threshold value while preventing video files from being compressed or deleted prior to an initial review by a user, the optimization engine being further configured to automatically modify the threshold value based on the viewing behavior to prevent video files from being compressed or deleted prior to an initial review of the video files by a user, wherein the threshold value is a period of time in which video is to be compressed or deleted and the viewing behavior includes a period of time that lapses before video is viewed.

9. The system of claim 8, wherein at least some of the video viewing workstations are at the first plurality of locations.

10. The system of claim 8, further including:

a secondary video storage means for converting the video files so that they occupy less storage space and to archive the converted video files, wherein the secondary video storage means compresses the video files by storing them in a reduced resolution format or deletes a predetermined percentage of the frames in each video file.

11. The system of claim 8, wherein the user-centric storage metric is a function of the rank or title of users accessing the video files.

12. The system of claim 8, wherein the enterprise-centric storage metric is based on a probability that video files of a predetermined type and age will be accessed.

13. A method of optimizing the storage of security video of a retail environment, the method comprising:

capturing security video footage at a plurality of retail locations within a retail enterprise;

transmitting the video footage for storage as video files at one or more centralized locations;

viewing the video files at a plurality of video viewing workstations within the retail enterprise;

tracking viewing behavior exhibited by a plurality of users at the viewing sites, the viewing behavior including the age and identities of the video files accessed;

providing an optimization engine to determine a user-centric storage metric and an enterprise-centric storage metric, wherein the user-centric storage metric is based on the frequency with which a distinct category of users accesses video files of a predetermined age at one or more of the video viewing workstations and wherein the enterprise-centric storage metric is based on viewing behavior of at least a representative sample of users within the enterprise, said optimization engine being configured to automatically determine whether to compress or delete video files based on the user-centric storage metric, the enterprise-centric storage metric and a threshold value while preventing video files from being compressed or deleted prior to an initial review by a user, wherein the threshold value is a period of time in which video is to be compressed or deleted and the viewing behavior includes a period of time that lapses before video is viewed; and

,

automatically modifying the threshold value based on the viewing behavior to prevent video files from being compressed or deleted prior to an initial review of the video files by a user.

14. The method of claim 13, wherein a determination is made to compress the video files by storing them in a reduced resolution or frame rate format.

15. The method of claim 13, further including the steps of:

determining, for each of a plurality of subsets of video files, the user-centric storage metric and the enterprise-centric storage metric; and

,

determining whether to archive each of the subsets of video files based on the user-centric storage metric, an enterprise-centric storage metric and the threshold value.

16. The method of claim 13, wherein the enterprise-centric storage metric is correlated to a probability that video files of a predetermined type and age will be accessed.

17. A system for optimizing security video storage, the system comprising:

a plurality of security video systems at a first plurality of locations within an enterprise;

a plurality of video viewing workstations at a second plurality of locations within the enterprise;

a user activity recorder to track viewing behavior of users at the video viewing workstations;

an optimization engine to determine a user-centric storage metric and an enterprise-centric storage metric, wherein the user-centric storage metric is based on the frequency with which a distinct category of users accesses video files of a predetermined age at one or more of the video viewing workstations and wherein the enterprise-centric storage metric is based on the viewing behavior of at least a representative sample of users within the enterprise, said optimization engine being configured to automatically determine whether to compress or delete video files based on the user-centric storage metric, the enterprise-centric storage metric and at least one threshold value, said optimization engine further being configured to automatically modify the at least one threshold value based on the viewing behavior of the selected user or group of users to prevent video from being compressed or deleted prior to an initial review by a user, the optimization engine being further configured to automatically modify the at least one threshold value based on the viewing behavior to prevent video files from being compressed or deleted prior to an initial review of the video files by a user, wherein the at least one threshold value is a period of time in which video is to be compressed or deleted and the viewing behavior of the selected user or group of users includes a period of time that lapses before video is viewed.