VIDEO MONITOR LAYOUT

• US 20180150479A1
• Filed: 05/11/2016
• Published: 05/31/2018
• Est. Priority Date: 05/29/2015
• Status: Active Grant

• Current Assignee: Zhejiang Uniview Technologies Co., Ltd.
• Original Assignee: Zhejiang Uniview Technologies Co., Ltd.
• Inventors: HE, Weiwei, LIU, Changji, YE, Qianyan, CHAI, Yaqin
• Granted Patent: US 10,445,348 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/38 Electronic maps specially adapted for navigation; Updating thereof
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06T 11/40 Filling a planar surface by adding surface attributes, e.g. colour or texture
• CPC Class Codes: G08B 13/196 using television cameras
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

A video monitor layout method and device are provided in the present disclosure. The method includes: determining a plurality of sample points on a map and determining a spatial range to be analyzed based on distribution regions of the plurality of sample points; obtaining grid units of the spatial range by rasterizing the spatial range to be analyzed; assigning a weight to each of the sample points, wherein the weight represents a level of monitor requirement at the sample point; and acquiring a weight value of each of the grid units according to the weight value of each of the sample points and a positional relationship between each of the sample points and each of the grid units and generating camera distribution position data of the spatial range based on the weight value of each of the grid units.

Claims

1. A method of laying out video monitors, comprising:

determining a plurality of sample points on a map;

determining a spatial range to be analyzed based on distribution regions of the plurality of sample points;

obtaining grid units of the spatial range by rasterizing the spatial range to be analyzed;

assigning a weight to each of the sample points, wherein the weight of each of the sample points represents a level of monitor requirement at each of the sample points; and

acquiring a weight value of each of the grid units according to the weight of each of the sample points and a positional relationship between each of the sample points and each of the grid units, and

generating camera distribution position data of the spatial range based on the weight value of each of the grid units.

2. The method according to claim 1, wherein assigning the weight to each of the sample points comprises:

determing a category of each of the sample points by classifying each of the sample points, and

assigning a weight to each of the sample points based on the category of each of the sample points,

wherein the weight is assigned to each of the sample points by using a hierarchical analyzing method in a case that the classification of the sample points has a plurality of levels.

3. The method according to claim 1, wherein acquiring the weight value of the grid unit according to the weight of each of the sample points and the positional relationship between each of the sample points and the grid unit comprises:

specifying a maximum influence distance of a single sample point on the map;

determining a weight component of the single sample point on the grid unit within its influence range according to the following formula;

4. The method according to claim 1, wherein determining the spatial range to be analyzed based on distribution regions of the sample points comprises:

determining maximum and minimum longitude and latitude values of all of the sample points; and

determining a region with map positions corresponding to the determined maximum and minimum longitude and latitude values as four vertices as the spatial range to be analyzed.

5. The method according to claim 1, wherein generating the camera distribution position data of the spatial range based on the weight value of each of the grid units comprises:

obtaining dimensionless weight raster data by nondimensionalizing the weight value of each of the grid units, wherein the dimensionless weight raster data comprise a dimensionless weight of each of the grid units;

obtaining a rendering diagram by rendering the dimensionless weight raster data, wherein different dimensionless weights are represented by different colors; and

generating a monitor layout requirement diagram of the spatial range by overlapping the rendering diagram to the spatial range on the map, and

generating the camera distribution position data of the spatial range based on the monitor layout requirement diagram.

6. The method according to claim 1, further comprising:

acquiring a monitor intensity matrix according to the camera distribution position data of the spatial range, wherein the monitor intensity matrix indicates respective camera monitor intensities at different spatial positions within the spatial range;

acquiring an operating intensity matrix according to camera operating log data of the spatial range, wherein the operating intensity matrix indicates respective camera operating intensities at different spatial positions within the spatial range;

calculating a correlation coefficient between the monitor intensity matrix and the operating intensity matrix; and

analyzing a degree of rationality of a camera distribution within the spatial range based on the correlation coefficient.

7. The method according to claim 6, wherein analyzing the degree of rationality of the camera distribution within the spatial range based on the correlation coefficient comprises:

determining a coefficient interval to which the correlation coefficient belongs by comparing the correlation coefficient with at least two preset coefficient intervals; and

determining the degree of rationality corresponding to the coefficient interval to which the correlation coefficient belongs as the degree of rationality of the camera distribution within the spatial range.

8. The method according to claim 6, wherein

the monitor intensity matrix comprises monitor intensity factors representing the camera monitor intensity at each spatial position within the spatial range, respectively;

the operating intensity matrix comprises operating intensity factors representing the camera operating intensity at each spatial position within the spatial range, respectively; and

the method further comprises;

obtaining an overlapping factor at the spatial position by conducting an overlapping operation on the monitor intensity factor and the operating intensity factor corresponding to a same spatial position, and

analyzing a degree of rationality of the camera distribution at each spatial position within the spatial range based on the overlapping factor.

9. The method according to claim 8, wherein

the overlapping operation comprises:

subtracting the operating intensity factor from the monitor intensity factor; and

analyzing the degree of rationality of the camera distribution at each spatial position within the spatial range based on the overlapping factor comprises;

determining that the camera distribution density at a spatial position within the spatial range is too high relative to the camera operating intensity at the spatial position when the overlapping factor is greater than a preset threshold value; and

determining that the camera distribution density at a spatial position within the spatial range is too low relative to the camera operating intensity at the spatial position when the overlapping factor is less than the preset threshold value.

10. A device for video monitor layout, comprising a processor that performs the following operations by reading and executing machine-executable instructions stored on a storage medium and corresponding to control logic of the video monitor layout:

determining a plurality of sample points on a map;

determining a spatial range to be analyzed based on distribution regions of the plurality of sample points;

obtaining grid units of the spatial range by rasterizing the spatial range to be analyzed;

assigning a weight to each of the sample points, wherein the weight of each of the sample points represents a level of monitor requirement at the sample point; and

acquiring a weight value of each of the grid units according to the weight of each of the sample points and a positional relationship between each of the sample points and each of the grid units; and

generating camera distribution position data of the spatial range based on the weight value of each of the grid units.

11. The device according to claim 10, wherein when acquiring the weight value of each of the grid units according to the weight value of each of the sample points and the positional relationship between each of the sample points and each of the grid units, the machine-executable instructions cause the processor to:

specify a maximum influence distance of a single sample point on the map;

determine a weight component of the single sample point on the grid unit within its influence range according to the following formula;

12. The device according to claim 10, wherein when determining the spatial range to be analyzed based on distribution regions of the sample points, the machine-executable instructions cause the processor to:

determine maximum and minimum longitude and latitude values of all of the sample points; and

determine a region with map positions corresponding to the determined maximum and minimum longitude and latitude values as four vertices as the spatial range to be analyzed.

13. The device according to claim 10, wherein when generating camera distribution position data of the spatial range based on the weight value of each of the grid units, the machine-executable instructions cause the processor to:

obtaining dimensionless weight raster data by nondimensionalizing the weight value of each of the grid units, wherein the dimensionless weight raster data comprise a dimensionless weight of each of the grid units;

obtaining a rendering diagram by rendering the dimensionless weight raster data, wherein different dimensionless weights are represented by different colors; and

generate a monitor layout requirement diagram of the spatial range overlapping the rendering diagram to the spatial range on the map, and

generate the camera distribution position data of the spatial range based on the monitor layout requirement diagram.

14. The device according to claim 10, wherein the machine-executable instructions further cause the processor to:

acquire a monitor intensity matrix according to the camera distribution position data of the spatial range, wherein the monitor intensity matrix indicates respective camera monitor intensities at different spatial positions within the spatial range;

acquire an operating intensity matrix according to camera operating log data of the spatial range, wherein the operating intensity matrix indicates respective camera operating intensities at different spatial positions within the spatial range;

calculate a correlation coefficient between the monitor intensity matrix and the operating intensity matrix and

analyze a degree of rationality of a camera distribution within the spatial range based on the correlation coefficient.

15. The device according to claim 14, wherein when analyzing the degree of rationality of the camera distribution within the spatial range based on the correlation coefficient, the machine-executable instructions cause the processor to:

determining a coefficient interval to which the correlation coefficient belongs by comparing the correlation coefficient with at least two preset coefficient intervals; and

determine the degree of rationality corresponding to the coefficient interval to which the correlation coefficient belongs as the degree of rationality of the camera distribution within the spatial range.