# US 10,321,160 B2 · Compressing multiple video files using localized camera meta data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,321,160 B2 - Document ID: US10321160B2 - Status: Granted - Kind: B2 - Application number: 15/648,595 - Filed: 2017-07-13 - Published: 2019-01-17 - Granted: 2019-06-11 - Earliest claimed: 2017-07-13 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Vijay Kumar Ananthapur Bache; Vijay Ekambaram; Sarbajit K. Rakshit; Saravanan Sadacharam - Web page: https://patentgrep.com/patent/US10321160B2 ## CPC - H04N 19/70: characterised by syntax aspects related to video coding, e.g. related to compression standards - H04N 1/32128: {attached to the image data, e.g. file header, transmitted message header, information on the same page or in the same computer file as the image (for information embedded in the image H04N1/32144)} - H04N 19/114: Adapting the group of pictures [GOP] structure, e.g. number of B-frames between two anchor frames (H04N19/107 takes precedence) - H04N 19/136: Incoming video signal characteristics or properties - H04N 19/146: Data rate or code amount at the encoder output - H04N 19/172: the region being a picture, frame or field - H04N 19/177: the unit being a group of pictures [GOP] - H04N 19/186: the unit being a colour or a chrominance component - H04N 23/60: Control of cameras or camera modules - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract An approach is provided for compressing video frames captured by a camera. A location, focal length, and direction of the camera, and the time of day during capture of the video frames (i.e., meta data) are determined. The meta data is associated with the video frames. Clusters of the video frames are determined, where the clusters have correlations to respective sets of values of the meta data. Based on multiple video frames within each of the clusters being compared with each other but not being compared with a video frame in another cluster, base and delta frames are determined and stored for each of the clusters. An amount of storage required for the base and delta frames is based in part on each of the correlations to the respective sets of values of the meta data. ## Claims ### Claim 1 A method of compressing video frames captured by a camera, the method comprising the steps of: a computer determining a location of the camera during a capture of the video frames by the camera, a focal length of the camera during the capture of the video frames, a direction of the camera during the capture of the video frames, and a time of day during the capture of the video frames; the computer associating meta data with the video frames captured by the camera, the meta data including the location of the camera, the focal length of the camera, the direction of the camera, and the time of day; the computer determining clusters of the video frames having correlations to respective sets of values of the meta data, each of the correlations exceeding a predetermined threshold value, based on a color space, a resolution, a frame rate, a refresh rate, and a bit rate of video files that include multiple video frames within each of the clusters, and based on an analysis of color balance and color intensity and an analysis of a texture of each of the multiple video frames within each of the clusters, the computer comparing the multiple video frames within each of the clusters without comparing the multiple video frames with a video frame in another cluster; and based on the multiple video frames within each of the clusters being compared with each other but not being compared with the video frame in another cluster, the computer determining a base frame and delta frames for each of the clusters, and storing the base frame and delta frames for each of the clusters, an amount of storage required for the base frame and delta frames for each of the clusters being based in part on each of the correlations to the respective sets of values of the meta data exceeding the predetermined threshold value. ### Claim 2 (depends on 1) The method of claim 1, further comprising the step of based on the base and delta frames, which were determined based on the multiple video frames within each of the clusters being compared with each other, the computer compressing the video frames captured by the camera. ### Claim 3 (depends on 2) The method of claim 2, wherein the step of compressing the video frames includes compressing the video frames across multiple video files. ### Claim 4 (depends on 1) The method of claim 1, further comprising the steps of: the computer determining times at which video frames included in a group of video frames were captured by the camera; and the computer determining a set of meta data associated with each of the video frames in the group, the set of meta data including a first value indicating a location of the camera at each of the times, a second value indicating a focal length of the camera at each the times, and a third value indicating a direction of the camera at each of the times; based on each of the video frames in the group being associated with the first, second, and third values, the computer determining that the camera points to a same field-of-view at each of the times; and based on the camera pointing to the same field-of-view at each of the times, the computer determining that the video frames included in the group share a similarity in visual properties that exceeds a threshold measurement of similarity. ### Claim 5 (depends on 1) The method of claim 1, wherein the steps of determining the clusters, comparing the multiple video frames, determining the base and delta frames, and storing the base and delta frames are performed during backup archiving of the video frames. ### Claim 6 (depends on 1) The method of claim 1, further comprising the steps of: the computer determining a correlation of a set of values of the meta data to a group of the video frames; based on the correlation, the computer determining a likelihood of the video frames in the group having similar visual properties; the computer determining that the likelihood of each of the video frames in the group exceeds a second predetermined threshold value; and based on the likelihood of the video frames in the group having similar visual properties exceeds the second predetermined threshold value, the computer determining one of the clusters of the video frames. ### Claim 7 (depends on 1) The method of claim 1, further comprising the step of: providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer readable program code in the computer, the program code being executed by a processor of the computer to implement the steps of determining the location, the focal length, and the direction of the camera, and the time of day, associating the meta data with the video frames, determining the clusters of the video frames, comparing the multiple video frames within each of the clusters, determining the base frame and the delta frames for each of the clusters, and storing the base frame and delta frames for each of the clusters. ### Claim 8 A computer program product, comprising: a computer readable storage medium; and a computer readable program code stored in the computer readable storage medium, the computer readable program code containing instructions that are executed by a central processing unit (CPU) of a computer system to implement a method of compressing video frames captured by a camera, the method comprising the steps of: the computer system determining a location of the camera during a capture of the video frames by the camera, a focal length of the camera during the capture of the video frames, a direction of the camera during the capture of the video frames, and a time of day during the capture of the video frames; the computer system associating meta data with the video frames captured by the camera, the meta data including the location of the camera, the focal length of the camera, the direction of the camera, and the time of day; the computer system determining clusters of the video frames having correlations to respective sets of values of the meta data, each of the correlations exceeding a predetermined threshold value, based on a color space, a resolution, a frame rate, a refresh rate, and a bit rate of video files that include multiple video frames within each of the clusters, and based on an analysis of color balance and color intensity and an analysis of a texture of each of the multiple video frames within each of the clusters, the computer system comparing the multiple video frames within each of the clusters without comparing the multiple video frames with a video frame in another cluster; and based on the multiple video frames within each of the clusters being compared with each other but not being compared with the video frame in another cluster, the computer system determining a base frame and delta frames for each of the clusters, and storing the base frame and delta frames for each of the clusters, an amount of storage required for the base frame and delta frames for each of the clusters being based in part on each of the correlations to the respective sets of values of the meta data exceeding the predetermined threshold value. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein the method implemented by the instructions being executed by the CPU further comprises the step of based on the base and delta frames, which were determined based on the multiple video frames within each of the clusters being compared with each other, the computer system compressing the video frames captured by the camera. ### Claim 10 (depends on 9) The computer program product of claim 9, wherein the step of compressing the video frames includes compressing the video frames across multiple video files. ### Claim 11 (depends on 8) The computer program product of claim 8, wherein the method implemented by the instructions being executed by the CPU further comprises the steps of: the computer system determining times at which video frames included in a group of video frames were captured by the camera; and the computer system determining a set of meta data associated with each of the video frames in the group, the set of meta data including a first value indicating a location of the camera at each of the times, a second value indicating a focal length of the camera at each the times, and a third value indicating a direction of the camera at each of the times; based on each of the video frames in the group being associated with the first, second, and third values, the computer system determining that the camera points to a same field-of-view at each of the times; and based on the camera pointing to the same field-of-view at each of the times, the computer system determining that the video frames included in the group share a similarity in visual properties that exceeds a threshold measurement of similarity. ### Claim 12 (depends on 8) The computer program product of claim 8, wherein the steps of determining the clusters, comparing the multiple video frames, determining the base and delta frames, and storing the base and delta frames are performed during backup archiving of the video frames. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein the method implemented by the instructions being executed by the CPU further comprises the steps of: the computer system determining a correlation of a set of values of the meta data to a group of the video frames; based on the correlation, the computer system determining a likelihood of the video frames in the group having similar visual properties; the computer system determining that the likelihood of each of the video frames in the group exceeds a second predetermined threshold value; and based on the likelihood of the video frames in the group having similar visual properties exceeds the second predetermined threshold value, the computer system determining one of the clusters of the video frames. ### Claim 14 A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; and a computer readable storage device coupled to the CPU, the storage device containing instructions that are executed by the CPU via the memory to implement a method of compressing video frames captured by a camera, the method comprising the steps of: the computer system determining a location of the camera during a capture of the video frames by the camera, a focal length of the camera during the capture of the video frames, a direction of the camera during the capture of the video frames, and a time of day during the capture of the video frames; the computer system associating meta data with the video frames captured by the camera, the meta data including the location of the camera, the focal length of the camera, the direction of the camera, and the time of day; the computer system determining clusters of the video frames having correlations to respective sets of values of the meta data, each of the correlations exceeding a predetermined threshold value, based on a color space, a resolution, a frame rate, a refresh rate, and a bit rate of video files that include multiple video frames within each of the clusters, and based on an analysis of color balance and color intensity and an analysis of a texture of each of the multiple video frames within each of the clusters, the computer system comparing the multiple video frames within each of the clusters without comparing the multiple video frames with a video frame in another cluster; and based on the multiple video frames within each of the clusters being compared with each other but not being compared with the video frame in another cluster, the computer system determining a base frame and delta frames for each of the clusters, and storing the base frame and delta frames for each of the clusters, an amount of storage required for the base frame and delta frames for each of the clusters being based in part on each of the correlations to the respective sets of values of the meta data exceeding the predetermined threshold value. ### Claim 15 (depends on 14) The computer system of claim 14, wherein the method implemented by the instructions being executed by the CPU further comprises the step of based on the base and delta frames, which were determined based on the multiple video frames within each of the clusters being compared with each other, the computer system compressing the video frames captured by the camera. ### Claim 16 (depends on 15) The computer system of claim 15, wherein the step of compressing the video frames includes compressing the video frames across multiple video files. ### Claim 17 (depends on 14) The computer system of claim 14, wherein the method implemented by the instructions being executed by the CPU further comprises the steps of: the computer system determining times at which video frames included in a group of video frames were captured by the camera; and the computer system determining a set of meta data associated with each of the video frames in the group, the set of meta data including a first value indicating a location of the camera at each of the times, a second value indicating a focal length of the camera at each the times, and a third value indicating a direction of the camera at each of the times; based on each of the video frames in the group being associated with the first, second, and third values, the computer system determining that the camera points to a same field-of-view at each of the times; and based on the camera pointing to the same field-of-view at each of the times, the computer system determining that the video frames included in the group share a similarity in visual properties that exceeds a threshold measurement of similarity. ### Claim 18 (depends on 14) The computer system of claim 14, wherein the steps of determining the clusters, comparing the multiple video frames, determining the base and delta frames, and storing the base and delta frames are performed during backup archiving of the video frames. ### Claim 19 (depends on 14) The computer system of claim 14, wherein the method implemented by the instructions being executed by the CPU further comprises the steps of: the computer system determining a correlation of a set of values of the meta data to a group of the video frames; based on the correlation, the computer system determining a likelihood of the video frames in the group having similar visual properties; the computer system determining that the likelihood of each of the video frames in the group exceeds a second predetermined threshold value; and based on the likelihood of the video frames in the group having similar visual properties exceeds the second predetermined threshold value, the computer system determining one of the clusters of the video frames.