# US 2019/0244341 A1 · Analysis apparatus, analysis method, and storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0244341 A1 - Document ID: US20190244341A1 - Status: Published application - Kind: A1 - Application number: 16/382,268 - Filed: 2019-04-12 - Published: 2019-08-08 - Earliest claimed: 2018-02-27 - Assignees: NEC Corporation - Applicants: NEC Corporation - Inventors: Jianquan Liu; Ka Wai Yung - Web page: https://patentgrep.com/patent/US20190244341A1 ## CPC - G06T 7/0002: {Inspection of images, e.g. flaw detection} - G06T 7/11: Region-based segmentation - G06T 7/187: involving region growing; involving region merging; involving connected component labelling - G06V 20/49: {Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes} - 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)} - G06Q 50/265: {Personal security, identity or safety} - G06T 2207/30242: Counting objects in image - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract The analysis apparatus (2000) includes a co-appearance event extraction unit (2020) and a frequent event detection unit (2040). The co-appearance event extraction unit (2020) extracts co-appearance events of two or more persons from each of a plurality of sub video frame sequences. The sub video frame sequence is included in a video frame sequence. The analysis apparatus (2000) may obtain the plurality of sub video frame sequences from one or more of the video frame sequences. The one or more of the video frame sequences may be generated by one or more of surveillance cameras. Each of the sub video frame sequences has a predetermined time length. The frequent event detection unit (2040) detects co-appearance events of the same persons occurring at a frequency higher than or equal to a pre-determined frequency threshold. ## Claims ### Claim 1 An analysis apparatus comprising: at least one memory storing instructions; and at least one processor executing the instructions to perform: extracting a co-appearance event from a video frame sequence, wherein the co-appearance event is that an unspecified combination of persons appears in the video frame sequence among a predetermined time window; and outputting information indicating the co-appearance event when the co-appearance event occurred at a frequency higher than or equal to a pre-determined threshold, wherein in at least one co-appearance event of the unspecified combination of persons, a first video frame from which a person is extracted is different from a second video frame from which another person is extracted. ### Claim 2 (depends on 1) The analysis apparatus according to claim 1, wherein the at least one processor further performs: creating an entry of the label in a people label table, wherein the people label table includes a label column and a count column, the label column indicating the label and the count column indicating a number of the label in the time window; for all feature-values in the video frame that just entered the time window, increasing their number by 1; and for all feature-values in the video frame that just left the time window, decreasing the number of the label by 1. ### Claim 3 (depends on 1) The analysis apparatus according to claim 1, wherein the at least one processor further performs: updating a count table for counting the co-appearance event, wherein the count table includes event column, count column, and latest update column, the event column indicating the co-appearance event, the count column indicating the frequency of the corresponding event, and the latest update column indicating a timestamp of the latest update of the co-appearance event. ### Claim 4 An analysis method comprising: extracting a co-appearance event from a video frame sequence, wherein the co-appearance event is that an unspecified combination of persons appears in the video frame sequence among a predetermined time window; and outputting information indicating the co-appearance event when the co-appearance event occurred at a frequency higher than or equal to a pre-determined threshold, wherein in at least one co-appearance event of the unspecified combination of persons, a first video frame from which a person is extracted is different from a second video frame from which another person is extracted. ### Claim 5 (depends on 4) The analysis method according to claim 4, further comprising: creating an entry of the label in a people label table, wherein the people label table includes a label column and a count column, the label column indicating the label and the count column indicating a number of the label in the time window; for all feature-values in the video frame that just entered the time window, increasing their number by 1; and for all feature-values in the video frame that just left the time window, decreasing the number of the label by 1. ### Claim 6 (depends on 4) The analysis method according to claim 4, further comprising: updating a count table for counting the co-appearance event, wherein the count table includes event column, count column, and latest update column, the event column indicating the co-appearance event, the count column indicating the frequency of the corresponding event, and the latest update column indicating a timestamp of the latest update of the co-appearance event. ### Claim 7 A non-statutory recording medium storing computer programs, the computer program causing a computer to perform: extracting a co-appearance event from a video frame sequence, wherein the co-appearance event is that an unspecified combination of persons appears in the video frame sequence among a predetermined time window; and outputting information indicating the co-appearance event when the co-appearance event occurred at a frequency higher than or equal to a pre-determined threshold, wherein in at least one co-appearance event of the unspecified combination of persons, a first video frame from which a person is extracted is different from a second video frame from which another person is extracted. ### Claim 8 (depends on 7) The non-statutory recording medium according to claim 7, wherein the computer program further causes the computer to perform: creating an entry of the label in a people label table, wherein the people label table includes a label column and a count column, the label column indicating the label and the count column indicating a number of the label in the time window; for all feature-values in the video frame that just entered the time window, increasing their number by 1; and for all feature-values in the video frame that just left the time window, decreasing the number of the label by 1. ### Claim 9 (depends on 7) The non-statutory recording medium according to claim 7, wherein the computer program further causes the computer to perform: updating a count table for counting the co-appearance event, wherein the count table includes event column, count column, and latest update column, the event column indicating the co-appearance event, the count column indicating the frequency of the corresponding event, and the latest update column indicating a timestamp of the latest update of the co-appearance event.