# US 2004/0156530 A1 · Linking tracked objects that undergo temporary occlusion > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2004/0156530 A1 - Document ID: US20040156530A1 - Status: Published application - Kind: A1 - Application number: 10/638,021 - Filed: 2003-08-08 - Published: 2004-08-12 - Earliest claimed: 2003-02-10 - Assignees: ActivEye, Inc. - Inventors: Tomas Brodsky; Yun-Ting Lin - Web page: https://patentgrep.com/patent/US20040156530A1 ## CPC - G06T 7/292: Multi-camera tracking - G06V 10/24: Aligning, centring, orientation detection or correction of the image - G06T 2207/30196: Human being; Person - G06T 2207/30232: Surveillance - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A method and system is configured to characterize regions of an environment by the likelihoods of transition of a target from each region to another. The likelihoods of transition between regions is preferably used in combination with conventional object-tracking algorithms to determine the likelihood that a newly-appearing object in a scene corresponds to a recently-disappeared target. The likelihoods of transition may be predefined based on the particular environment, or may be determined based on prior appearances and disappearances in the environment, or a combination of both. The likelihoods of transition may also vary as a function of the time of day, day of the week, and other factors that may affect the likelihoods of transitions between regions in the particular surveillance environment. ## Claims ### Claim 1 A method that facilitates tracking of a target, comprising: detecting a disappearance of the target from a first region of a scene in a field of view of a camera, detecting an appearance of an object in a second region of the scene, and estimating a likelihood of the object corresponding to the target, based on a transition likelihood that is associated with object transitions from the first region to the second region. ### Claim 2 (depends on 1) The method of claim 1, further including: detecting an appearance of an other object in an other region of the scene, and estimating a likelihood of the other object corresponding to the target, based on a transition likelihood that is associated with object transitions from the first region to the other region. ### Claim 3 (depends on 2) The method of claim 2, further including comparing: a first measure based on the likelihood of the object corresponding to the target to a second measure based on the likelihood of the other object corresponding to the target, to affect thereby a determination of whether to link the object or the other object to the target. ### Claim 4 (depends on 3) The method of claim 3, wherein the determination of whether to link the object or the other object to the target is also based on a likelihood of a further object corresponding to the target. ### Claim 5 (depends on 1) The method of claim 1, further including: detecting an appearance of an other object in an other region of an other scene in a field of view of an other camera, and estimating a likelihood of the other object corresponding to the target, based on a transition likelihood that is associated with object transitions from the first region to the other region. ### Claim 6 (depends on 1) The method of claim 1, further including linking the object as the target for subsequent tracking, based on: the likelihood of the object corresponding to the target, and at least one measure of similarity between the object and the target. ### Claim 7 (depends on 6) The method of claim 6, wherein the at least one measure of similarity is based on at least one of: colors of the object and the target, sizes of the object and the target, shapes of the object and the target, orientations of the object and the target, and motions of the object and the target. ### Claim 8 (depends on 1) The method of claim 1, wherein the disappearance of the target occurs at a first time, the appearance of the object occurs at a second time, and the likelihood of the object corresponding to the target is further dependent upon a time duration between the first time and the second time. ### Claim 9 (depends on 8) The method of claim 8, further including determining the transition likelihood, based on prior disappearances and subsequent appearances in one or more scenes, and further based on time durations between the prior disappearances and subsequent appearances. ### Claim 10 (depends on 9) The method of claim 9, further including determining the transition likelihood, based on a speed of the object. ### Claim 11 (depends on 1) The method of claim 1, further including determining the transition likelihood, based on prior disappearances and subsequent appearances in one or more scenes. ### Claim 12 (depends on 11) The method of claim 11, wherein determining the transition likelihood is further based on a predetermined likelihood of transition between the first region and the second region. ### Claim 13 (depends on 12) The method of claim 12, wherein determining the transition likelihood is based on a weighted running average that is based on the predetermined likelihood, the prior disappearances and subsequent appearances, and a result of a current disappearance. ### Claim 14 (depends on 11) The method of claim 11, wherein determining the transition likelihood is based on a ratio of a number of prior transitions from the first region to the second region to a total number of disappearances from the first region. ### Claim 15 (depends on 11) The method of claim 11, wherein determining the transition likelihood is based on a ratio of a number of prior transitions from the first region to the second region to a total number of appearances at the second region. ### Claim 16 (depends on 15) The method of claim 15, wherein determining the transition likelihood is further based on a ratio of a number of prior transitions from the first region to the second region to a total number of disappearances from the first region. ### Claim 17 A method of characterizing a plurality of regions of a scene, to facilitate object-tracking among the plurality of regions, including: determining a number of transitions of objects from each region to each other region, and determining a transition likelihood of objects from each region to each other region, based on the number of transitions of objects from each region to each other region. ### Claim 18 (depends on 17) The method of claim 17, further including: determining at least one of: a number of arrivals of objects in each region, and a number of departures of objects in each region; and wherein determining the transition likelihood is further based on at least one of the number of arrivals and departures of objects in each region. ### Claim 19 (depends on 18) The method of claim 18, wherein determining the transition likelihood is further based on a predetermined likelihood of transition between each region and each other region. ### Claim 20 (depends on 19) The method of claim 19, wherein determining the transition likelihood is based on a weighted running average that is based on the transition likelihood, and a result of a current disappearance. ### Claim 21 (depends on 18) The method of claim 18, wherein determining the transition likelihood is based on a ratio of the number of transitions from each region to the number of departures from each region. ### Claim 22 (depends on 18) The method of claim 18, wherein determining the transition likelihood is based on a ratio of the number of transitions to each region to the number of arrivals to each region. ### Claim 23 (depends on 22) The method of claim 22, wherein determining the transition likelihood is further based on a ratio of a number of transitions from each region to the number of departures from each region. ### Claim 24 A system that facilitates tracking of objects among a plurality of regions of one or more scenes, comprising: a video processor that is configured to identify arrivals and departures of objects in each region of the plurality of regions, a transition predictor, operably coupled to the video processor, that is configured to provide a measure of likelihood that a departure of a first object from a first region of the plurality of regions corresponds to an arrival of a second object at a second region of the plurality of regions, an object comparer, operably coupled to the video processor, that is configured to provide a measure of similarity between the first object and the second object, and an object linker, operably coupled to the transition predictor and the object comparer, that is configured to selectively link data associated with the second object to data associated to the first object, based on the measures of likelihood and similarity. ### Claim 25 (depends on 24) The system of claim 24, further including a display processor, operably coupled to the video processor and the object linker, that is configured to display some or all of the one or more scenes dependent upon the linking of the data associated with the second object to the data associated with the first object. ### Claim 26 (depends on 24) The system of claim 24, wherein the measure of likelihood is based on prior disappearances and subsequent appearances among the plurality of regions ### Claim 27 (depends on 24) The system of claim 24, wherein object linker is further configured to selectively link data associated with the second object to data associated to the first object based on measures of likelihood and similarity of other objects to the second object. ### Claim 28 (depends on 24) The system of claim 24, wherein the measure of similarity is based on at least one of: colors of the first and second objects, sizes of the first and second objects, shapes of the first and second objects, orientations of the first and second objects, and motions of the first and second objects. ### Claim 29 (depends on 24) The system of claim 24, wherein the disappearance of the first object occurs at a first time, the appearance of the second object occurs at a second time, and the measure of likelihood is dependent upon a time duration between the first time and the second time. ### Claim 30 (depends on 24) The system of claim 24, wherein the measure of likelihood is based on prior disappearances and subsequent appearances among the plurality of regions, and further based on time durations between the prior disappearances and subsequent appearances. ### Claim 31 (depends on 30) The system of claim 30, wherein the measure of likelihood is further based on a speed of the first object.