IP Library Granted Patent US 11,917,282
Granted Patent B2
US 11,917,282 · App. 17/743,622 · Granted Feb 27, 2024

Usage-based assessment for surveillance storage configuration

Inventors: Shaomin Xiong (Newark, CA); Toshiki Hirano (San Jose, CA)
Assignee: Western Digital Technologies, Inc.
H04N23/61H04N7/185H04N7/188H04N23/631
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Quick Facts
Patent No.
US 11,917,282
App. No.
17/743,622
Granted
Feb 27, 2024
Kind
B2
Abstract

Systems and methods for site-based estimation of storage requirements, such as for surveillance video cameras, are described. Product information, a data retention policy, and an intended recording mode about a camera of a surveillance system may be received through a user interface of a user device. A baseline storage value is determined based on the received product information and the data retention policy. A storage requirement may be calculated based on the baseline data storage value and a determined recording co-efficient value based on a sample scene at the camera location. Scene descriptors may be generated based on the sample scene to retrieve the recording co-efficient value from a lookup table.

Claims (151)

1. A system, comprising:

a processor;

a memory;

a scene description controller configured to:

receive scene video data depicting a view from a video image sensor at a camera location;

determine, based on the scene video data, a scene description comprising at least one scene descriptor; and

determine, based on the scene description, a category of scene activity of the view;

a data storage estimator configured to:

determine a baseline data storage value based on a data storage plan associated with the video image sensor;

determine a recording coefficient value based on the determined category of scene activity; and

calculate a storage requirement based on:

the baseline data storage value; and

the recording coefficient value; and

a user interface data presenter configured to present the calculated storage requirement through a user interface of a user device.

2. The system of claim 1 , wherein:

the data storage estimator is further configured to:

receive product information about the video image sensor; and

determine a data retention policy for the video image sensor; and

the baseline data storage value is further based on the product information and the data retention policy.

3. The system of claim 1 , further comprising:

a video camera housing, wherein the video camera housing encloses:

the video image sensor; and

a surveillance controller configured to:

receive video data from the video image sensor; and

send, to the scene description controller, scene video data depicting the view from the video image sensor.

4. The system of claim 1 , further comprising:

an object detector, wherein:

the object detector includes:

a motion model configured to determine a bounding box of moving objects in the scene video data; and

an image classifier configured to detect an object of interest in the scene video data; and

the scene description controller is further configured to:

compare bounding boxes of moving objects to reference scene data retrieved from a reference data source;

determine a metric of activity based on the comparison and the camera location; and

determine the category of scene activity responsive to the metric of activity exceeding a predetermined threshold.

5. The system of claim 1 , wherein the scene description controller is further configured to:

receive aggregated video data and regional identifiers;

generate a coefficient lookup data structure of a plurality of coefficient values based on determined scene activity data from the aggregated video data;

determine a representative coefficient value of the plurality of coefficient values for each scene descriptor value and corresponding regional identifier; and

store the representative coefficient value for each scene descriptor value and corresponding regional identifier in the co efficient lookup data structure table.

6. The system of claim 5 , wherein:

the scene description controller is further configured to:

count a number of triggers in the scene video data using a moving object detector; and

determine the category of scene activity based on the number of triggers in the scene video data; and

the recording coefficient value in the coefficient lookup data structure is based on the number of triggers.

7. The system of claim 1 , wherein:

the scene description controller is further configured to determine the scene description based on an analysis of the scene video data;

the analysis comprises selecting at least one scene descriptor from a set of scene descriptors that includes a plurality of scene descriptors selected from:

outdoor;

indoor;

doorbell;

garage;

window;

balcony;

commercial;

residential;

industrial; and

office; and

each scene descriptor is associated with a representative recording coefficient value in a coefficient lookup table.

8. The system of claim 1 , wherein the scene description controller is further configured to receive the scene video data from at least one of:

a camera on the user device; and

the video image sensor at the camera location.

9. The system of claim 1 , further comprising:

a user interface data selector, wherein:

the user interface data selector includes a video format selector configured to receive at least one of:

a user selection of video compression format;

a user selection of video quality;

a user selection of video resolution; and

a user selection of a number of frames per second; and

the data storage estimator is further configured to:

determine an updated baseline data storage value based on at least one of the user selection of video compression format, the user selection of video quality, the user selection of video resolution, and the user selection of the number of frames per second; and

determine the storage requirement based the updated baseline data storage value.

10. The system of claim 1 , further comprising:

a user interface data selector, wherein:

the user interface data selector includes:

a data retention policy selector configured to receive at least one of:

a number of days to store video data; and

a number of hours per day to store video data; and

a camera enumeration selector configured to receive a number of cameras; and

the data storage estimator is further configured to:

determine an updated baseline data storage value based on at least one of the received number of days to store video data, the received number of hours per day to store video data, and the received number of cameras; and

determine the storage requirement based the updated baseline data storage value.

11. The system of claim 1 , further comprising:

a user interface data selector configured to receive a product information indicator selected from:

a web link describing product information associated with the video image sensor; and

a user-inputted model number associated with the video image sensor;

wherein the data storage estimator is further configured to:

retrieve a set of product information values based on the product information indicator, wherein the set of product information values includes at least one of:

a video compression format data value;

a video quality data value;

a video resolution data value;

a frames per second data value;

a night vision data value;

a recording type data value;

a supported storage medium data value;

a maximum storage data value; and

a storage plan data value;

determine an updated baseline data storage value based on at least one product information value of the set of product information values; and

calculate the storage requirement based on the updated baseline data storage value.

12. The system of claim 1 , wherein the data storage estimator is further configured to:

determine a plan coefficient value associated with the data storage plan; and

calculate the storage requirement based on the plan coefficient value.

13. The system of claim 1 , further comprising:

a data lookup data structure generator configured to:

receive, over a network, aggregated data associated with storage requirements for other systems located in a same region as the video image sensor;

determine at least one recording coefficient value based on the aggregated data; and

store the at least one recording coefficient value in a coefficient lookup data structure.

14. A computer-implemented method, comprising:

determining a baseline data storage value based on a data storage plan for a video camera at a camera location;

receiving scene video data depicting a view at the camera location;

determining, based on the scene video data, a scene description comprising at least one scene descriptor;

determining a category of scene activity of the view based on the scene description;

determining a recording coefficient value based on the determined category of scene activity of the view;

calculating a storage requirement based on:

the baseline data storage value; and

the recording coefficient value; and

presenting the calculated storage requirement on a user interface of a user device.

15. The computer-implemented method of claim 14 , further comprising:

determining, for the video camera, a data retention policy based on a selected time period; and

receiving product information about the video camera, wherein the baseline data storage value is further based on the data retention policy and the product information.

16. The computer-implemented method of claim 14 , further comprising:

determining, using an object detection model, verification object data for detected objects in the scene video data;

comparing the verification object data for the detected objects to reference scene data retrieved from a reference data source;

determining a metric of activity based on the comparison and the camera location; and

determining the category of scene activity responsive to the metric of activity exceeding a predetermined threshold.

17. The computer-implemented method of claim 14 , further comprising:

determining an updated baseline data storage value based on at least one of:

a received number of days to store video data;

a received number of hours per day to store video data; and

a received number of cameras; and

determining the storage requirement based the updated baseline data storage value.

18. The computer-implemented method of claim 14 , further comprising:

retrieving a set of product information values based on at least one of:

a user-inputted model number; and

a received web link;

determining an updated baseline data storage value based on at least one product information value from the set of product information values; and

calculating the storage requirement based on the updated baseline data storage value.

19. The computer-implemented method of claim 14 , further comprising:

determining a plan coefficient value associated with a data storage plan; and

calculating the storage requirement based on the plan coefficient value.

20. A system, comprising:

a processor;

a memory;

means for determining a baseline data storage value based on a data storage plan for a video camera at a camera location;

means for receiving scene video data depicting a view at the camera location;

means for determining, based on the scene video data, a scene description comprising at least one scene descriptor;

means for determining a category of scene activity of the view based on the scene description;

means for determining a recording coefficient value based on the determined category of scene activity of the view;

means for calculating a storage requirement based on:

the baseline data storage value; and

the recording coefficient value; and

means for presenting the calculated storage requirement on a user interface of a user device.

Assignments (8)
PARTIAL RELEASE OF SECURITY INTERESTS Recorded Apr 25, 2025
From: JPMORGAN CHASE BANK, N.A., AS AGENT
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 071382/0001 →
SECURITY AGREEMENT Recorded Apr 25, 2025
From: SANDISK TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 071050/0001 →
PATENT COLLATERAL AGREEMENT Recorded Aug 23, 2024
From: SANDISK TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A., AS THE AGENT
Reel/Frame 068762/0494 →
CHANGE OF NAME Recorded Jun 27, 2024
From: SANDISK TECHNOLOGIES, INC.
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 067982/0032 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 29, 2024
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: SANDISK TECHNOLOGIES, INC.
Reel/Frame 067567/0682 →
PATENT COLLATERAL AGREEMENT - A&R LOAN AGREEMENT Recorded Aug 21, 2023
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 064715/0001 →
PATENT COLLATERAL AGREEMENT - DDTL LOAN AGREEMENT Recorded Aug 21, 2023
From: WESTERN DIGITAL TECHNOLOGIES, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 067045/0156 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 13, 2022
From: XIONG, SHAOMIN; HIRANO, TOSHIKI
To: WESTERN DIGITAL TECHNOLOGIES, INC.
Reel/Frame 059899/0804 →