Tracking moving objects using a camera network
US-9615064-B2 · Apr 4, 2017 · US
US11367330B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11367330-B2 |
| Application number | US-202017032429-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 25, 2020 |
| Priority date | Apr 26, 2013 |
| Publication date | Jun 21, 2022 |
| Grant date | Jun 21, 2022 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
An information processing system is provided. The information processing system comprises at least one processor configured to receive inputs of videos captured by a plurality of imaging apparatuses, detect a first person image appearing in a first video captured by a first imaging apparatus and a second person image appearing in a second video captured by a second imaging apparatus, associate a first person with a second person based on a first feature value of the first person and a second feature value of the second person, and provide an elapsed time from a first time point when the first person disappears from the first video to a second time point when the second person appears in the second video. The first feature value and the second feature value may include information based on histogram.
Opening claim text (preview).
The invention claimed is: 1. An information processing system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to: receive inputs of videos captured by a plurality of imaging apparatuses; detect a first person image appearing in a first video captured by a first imaging apparatus among the plurality of imaging apparatuses and a second person image appearing in a second video captured by a second imaging apparatus among the plurality of imaging apparatuses; associate a first person with a second person, based on a first feature value of the first person and a second feature value of the second person; and provide an elapsed time from a first time point when the first person disappears from the first video to a second time point when the second person appears in the second video, wherein the first feature value and the second feature value include information based on histogram. 2. The information processing system according to claim 1 , wherein the elapsed time is provided after the first person is associated with the second person, based on the first feature value of the first person and the second feature value of the second person. 3. The information processing system according to claim 1 , wherein the at least one processor is further configured to execute the instructions to control a display device to display an image that includes the second person who is set as a monitoring target being highlighted, wherein a person appears in at least one of the first video and the second video, and is associated with a person appearing in another video. 4. The information processing system according to claim 3 , wherein the at least one processor is further configured to execute the instructions to change a manner to highlight the second person included in the image, based on the elapsed time and a similarity between the first feature value and the second feature value. 5. The information processing system according to claim 4 , wherein the at least one processor is further configured to execute the instructions to: compute the similarity, wherein the elapsed time is provided after the similarity is computed. 6. The information processing system according to claim 4 , wherein the at least one processor is further configured to execute the instructions to: compute a first probability indicating that the first person and the second person are same based on the similarity, and a second probability that the first person and the second person are not the same based on the elapsed time, wherein the manner to highlight the second person included in the image is changed, based on a result of comparison between the first probability and the second probability. 7. An information processing method performed by at least one computer, the method comprising: receiving inputs of videos captured by a plurality of imaging apparatuses; detecting a first person image appearing in a first video captured by a first imaging apparatus among the plurality of imaging apparatuses and a second person image appearing in a second video captured by a second imaging apparatus among the plurality of imaging apparatuses; associating a first person with a second person, based on a first feature value of the first person and a second feature value of the second person; and providing an elapsed time from a first time point when the first person disappears from the first video to a second time point when the second person appears in the second video, wherein the first feature value and the second feature value include information based on histogram. 8. The information processing method according to claim 7 , wherein the elapsed time is provided after the first person is associated with the second person, based on the first feature value of the first person and the second feature value of the second person. 9. The information processing method according to claim 7 , further comprising: controlling a display device to display an image that includes the second person who is set as a monitoring target being highlighted, wherein a person appears in at least one of the first video and the second video, and is associated with a person appearing in another video. 10. The information processing method according to claim 9 , further comprising: changing a manner to highlight the second person included in the image, based on the elapsed time and a similarity between the first feature value and the second feature value. 11. The information processing method according to claim 10 , further comprising: computing the similarity, wherein the elapsed time is provided after the similarity is computed. 12. The information processing method according to claim 10 , further comprising computing a first probability indicating that the first person and the second person are same based on the similarity, and a second probability that the first person and the second person are not the same based on the elapsed time, wherein the manner to highlight the second person included in the image is changed, based on a result of comparison between the first probability and the second probability. 13. A non-transitory computer readable recording medium storing programs, the programs causing at least one computer to perform: receiving inputs of videos captured by a plurality of imaging apparatuses; detecting a first person image appearing in a first video captured by a first imaging apparatus among the plurality of imaging apparatuses and a second person image appearing in a second video captured by a second imaging apparatus among the plurality of imaging apparatuses; associating a first person with a second person, based on a first feature value of the first person and a second feature value of the second person; and providing an elapsed time from a first time point when the first person disappears from the first video to a second time point when the second person appears in the second video, wherein the first feature value and the second feature value include information based on histogram. 14. The non-transitory computer readable recording medium according to claim 13 , wherein the elapsed time is provided after the first person is associated with the second person, based on the first feature value of the first person and the second feature value of the second person. 15. The non-transitory computer readable recording medium according to claim 13 , wherein the programs further causes the computer to perform: controlling a display device to display an image that includes the second person who is set as a monitoring target being highlighted, wherein a person appears in at least one of the first video and the second video, and is associated with a person appearing in another video. 16. The non-transitory computer readable recording medium according to claim 15 , wherein the programs further causes the computer to perform: changing a manner to highlight the second person included in the image, based on the elapsed time and a similarity between the first feature value and the second feature value. 17. The non-transitory computer readable recording medium according to claim 16 , wherein the programs further causes the computer to perform: computing the similarity, wherein the elapsed time is provided after the similarity is computed. 18. The non-transitory computer readable recording medium according to claim 16 , wherein the programs further causes the computer to perform: computing a first probability indicating that
using television cameras · CPC title
Recognition of crowd images, e.g. recognition of crowd congestion · CPC title
for receiving images from a plurality of remote sources · CPC title
in albums, collections or shared content, e.g. social network photos or video · CPC title
Multiple cameras, each having view on one of a plurality of scenes, e.g. multiple cameras for multi-room surveillance or for tracking an object by view hand-over · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.