1. A system for tracking a person in a pre-defined area, the pre-defined area comprising a plurality of imaging devices, each of the plurality of imaging devices being located at a corresponding pre-defined location, the system comprising:
a. an image receiving module configured for:
i. receiving a first image of a lower portion of the person, the first image being captured by a first imaging device at a first location in the pre-defined area;
ii. receiving a second image of the lower portion of the person, the second image being captured by a second imaging device at a second location in the pre-defined area;
b. an image processing module configured for recognizing the person at the second location by comparing the first image and the second image; and
c. a location module configured for locating the recognized person based on the second location.
2. The system according to claim 1 further comprising a memory module configured for storing at least one of the first image and at least one personal detail, the at least one personal detail being associated with the person.
3. The system according to claim 1 further comprising an input module configured for receiving at least one personal detail of the person at the first location.
4. The system according to claim 3 further comprising an associating module configured for associating the first image with the at least one personal detail at the first location, wherein the association facilitates defining the person in the pre-defined area.
5. The system according to claim 3 further comprising an identification module configured for identifying the person based on the at least one personal detail, the first image and the second image.
6. The system according to claim 3 further comprising a communication module configured for sending a message to a communication device of the person, the message being sent on the at least one personal detail, wherein the message comprises at least one information corresponding to the pre-defined location of the second imaging device.
7. The system according to claim 1, wherein the image processing module is further configured for dividing each of the first image and the second image into corresponding one or more pre-defined image segments.
8. The system according to claim 7, wherein the image processing module compares the first image and the second image by comparing at least one of the one or more pre-defined image segments associated with the first image with the corresponding at least one of one or more pre-defined image segments associated with the second image.
9. The system according to claim 8, wherein the image processing module compares at least one of the one or more pre-defined image segments associated with the first image with the corresponding at least one of one or more pre-defined image segments associated with the second image based on one or more image processing algorithms, each of the one or more image processing algorithms being associated with the corresponding one or more pre-defined image segments based on one or more image characteristics of the one or more pre-defined image segments.
10. The system according to claim 1 further comprising a tag module configured for associating each of the first image and the second image with corresponding one or more identification tags.
11. The system according to claim 10 further comprising an analysis module configured for comparing each of the one or more identification tags associated with the first image with the corresponding each of the one or more identification tags associated with the second image, wherein the comparison of the one or more identification tags associated with each of the first image and the second image facilitates identification of the person.
12. The system according to claim 1 further comprising a trend module configured for analyzing a movement trend of the person in the pre-defined area based on the location of the person.
13. The system according to claim 12, wherein the trend module is further configured for analyzing the movement trend of the person based on the corresponding pre-defined location and one or more identification tags associated with each of the first image and the second image.
14. The system according to claim 12, wherein the trend module is further configured to analyze the movement trend corresponding to each visit made by the person to the shopping store, each movement trend being associated to the person based on at least one personal detail, the at least one person detail being associated with the person.
15. A method for tracking a person in a pre-defined area, the pre-defined area comprising a plurality of imaging devices, each of the plurality of imaging devices being located at a corresponding pre-defined location, the method comprising:
a. receiving a first image of a lower portion of the person, the first image being captured by a first imaging device at a first location in the pre-defined area;
b. receiving a second image of the lower portion of the person, the second image being captured by a second imaging device at a second location in the pre-defined area;
c. recognizing the person at the second location based on the comparison between the first image and the second image; and
d. locating the recognized person based on the second location.
16. The method according to claim 15 further comprising receiving at least one personal detail of the person at the first location.
17. The method according to claim 16 further comprising associating the first image with the at least one personal detail of the person at the first location, wherein the association facilitates defining the person in the pre-defined area.
18. The method according to claim 16 further comprising identifying the person based on the at least one personal detail, the first image and the second image.
19. The method according to claim 16, wherein the at least one personal detail is at least one of a mobile number, an email address, a residential address, a membership number, and a unique identification number.
20. The method according to claim 16 further comprising sending a message to a communication device of the person, the message being sent on the at least one personal detail, wherein the message comprises at least one information corresponding to the pre-defined location of the second imaging device.
21. The method according to claim 20, wherein the at least one information is at least one of one or more promotions, at least one product location and one or more product details, the pre-defined area being a shopping complex.
22. The method according to claim 15 further comprising dividing each of the first image and the second image into corresponding one or more pre-defined image segments.
23. The method according to claim 22, wherein the comparison between the first image and the second image comprises comparing at least one of the one or more pre-defined image segments associated with the first image with the corresponding at least one of the one or more pre-defined image segments associated with the second image.
24. The method according to claim 23, wherein at least one of the one or more pre-defined image segments associated with the first image is compared with the corresponding at least one of one or more pre-defined image segments associated with the second image based on one or more image processing algorithms, each of the one or more image processing algorithms being associated with the corresponding one or more pre-defined image segments based on one or more image characteristics of the one or more pre-defined image segments.
25. The method according to claim 15 further comprising associating each of the first image and the second image with corresponding one or more identification tags.
26. The method according to claim 25, wherein recognizing the person at the second location further comprises:
a. analyzing the comparison between the first image and the second image based on the associated one or more identification tags; and
b. identifying the person based on the analyzed comparison.
27. The method according to claim 25, wherein at least one identification tag of the one or more identification tags is a time-stamp corresponding to each of the first image and the second image.
28. The method according to claim 15 further comprising analyzing a movement trend of the person in the pre-defined area based on the location of the person.
29. The method according to claim 28 further comprising analyzing the movement trend of the person in the pre-defined area based on the corresponding location and one or more identification tags associated with each of the first image and the second image.
30. The method according to claim 28 further comprising analyzing the movement trend corresponding to each visit made by the person to the shopping store, each movement trend being associated to the person based on at least one personal detail, the at least one person detail being associated with the person.
31. A computer program product for use with a computer, the computer program product comprising a set of instructions stored in a computer usable medium having a computer readable program code embodied therein for tracking a person in a pre-defined area, the pre-defined area comprising a plurality of imaging devices, each of the plurality of imaging devices being located at a corresponding pre-defined location, the computer readable program code performing:
a. receiving a first image of a lower portion of the person, the first image being captured by a first imaging device at a first location in the pre-defined area;
b. receiving a second image of the lower portion of the person, the second image being captured by a second imaging device at a second location in the pre-defined area;
c. recognizing the person at the second location based on the comparison between the first image and the second image; and
d. locating the recognized person based on the second location.
32. The computer program product of claim 31 further performing receiving at least one personal detail of the person at the first location.
33. The computer program product of claim 32 further performing associating the first image with the at least one personal detail of the person at the first location, wherein the association facilitates defining the person in the pre-defined area.
34. The computer program product of claim 32 further performing identifying the person based on the at least one personal detail, the first image and the second image.
35. The computer program product of claim 32 further performing sending a message to a communication device of the person, the message being sent on the at least one personal detail, wherein the message comprises at least one information corresponding to the pre-defined location of the second imaging device.
36. The computer program product of claim 31 further performing dividing each of the first image and the second image into corresponding one or more pre-defined image segments.
37. The computer program product of claim 36, wherein the computer readable program code further performs comparing at least one of the one or more pre-defined image segments associated with the first image with the corresponding at least one of one or more pre-defined image segments associated with the second image.
38. The computer program product of claim 37, wherein the computer readable program code further performs comparing at least one of the one or more pre-defined image segments associated with the first image with the corresponding at least one of one or more pre-defined image segments associated with the second image based on one or more image processing algorithms, each of the one or more image processing algorithms being associated with the corresponding one or more pre-defined image segments based on one or more image characteristics of the one or more pre-defined image segments.
39. The computer program product of claim 31 further performing associating each of the first image and the second image with corresponding one or more identification tags.
40. The computer program product of claim 39, wherein the computer readable program code further performs recognizing the person at the second location further performing:
a. analyzing the comparison between the first image and the second image based on the associated one or more identification tags; and
b. identifying the person based on the analyzed comparison.
41. The computer program product of claim 31 further performing analyzing a movement trend of the person in the pre-defined area based on the location of the person.
42. The computer program product of claim 41 further performing analyzing the movement trend of the person in the pre-defined area based on the corresponding location and one or more identification tags associated with each of the first image and the second image.
43. The computer program product of claim 41 further performing analyzing the movement trend corresponding to each visit made by the person to the shopping store, each movement trend being associated to the person based on at least one personal detail, the at least one person detail being associated with the person.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method, comprising:
obtaining a signal that includes a plurality of cycles;
generating a map that maps motion phases to the signal based on both an amplitude and a slope of the signal, wherein the map divides each cycle into a descending region and an ascending region, and the descending region includes a portion of the signal with a negative slope between a lesser of a cycle maximum and a mean of signal maxima of the plurality of cycles and a greater of a cycle minimum and a mean of signal minima of the plurality of cycles, and the ascending region includes a second portion of the signal with a positive slope between the lesser of the cycle maximum and the mean of the signal maxima and the greater of the cycle minimum and the mean of the signal minima; and
generating volumetric image data based on data acquired by a scanner and the mapped motions phases.
2. The method of claim 1, further comprising:
identifying a set of timestamps for the plurality of cycles for a predetermined phase of interest based on the map, wherein identified set of timestamps corresponds to a common signal amplitude; and
generating a signal indicative thereof.
3. The method of claim 1, wherein the signal is detected while imaging a moving object having recurring cyclic motion and a plurality of cycles corresponding to the recurring cyclic motion having irregular periodicity.
4. The method of claim 1, wherein the object is a subject and the signal is indicative of multiple breathing or cardiac cycles of the subject.
5. The method of claim 1, wherein the scanner includes at least one of a CT scanner, an X-ray scanner, a Positron Emission Tomography (PET) scanner, a Single Photon Emission Computed Tomography (SPECT) scanner, a Magnetic Resonance Imaging (MRI) scanner, or an Ultrasound (US) scanner; and
wherein generating volumetric image data includes:
selecting at least one mapped phase;
selecting data acquired by the scanner according to the at least one selected phase; and
reconstructing selected data in he volumetric image data.
6. The method of claim 1, wherein the descending amplitude region corresponds to one of contraction or expansion of the object and the ascending amplitude region corresponds to the other of expansion or contraction of the object.
7. The method of claim 1, wherein the phases span from 0% to 99% over the cycle, and one set of phases ranges from 0% to 49% and correspond to at least one of the ascending region or the descending region and another set of phases ranges from 50% to 99% and correspond to the other of the least one of the ascending region or the descending region.
8. The method of claim 1, further comprising:
identifying the signal maxima and minima for the plurality of cycles;
determining the mean signal maximum and the mean signal minimum respectively based on the identified signal maxima and minima; and
mapping the phases to the amplitude of each cycle in a range spanning from the lesser of the mean signal maximum and the cycle maximum to the greater of the mean signal minimum and the cycle minimum.
9. The method of claim 1, further comprising:
identifying a maximum for an evaluation range within a cycle, wherein the maximum corresponds to a point lying between two points with amplitudes below a predetermined threshold;
comparing points in the evaluation range before and after the maximum with the maximum;
identifying the maximum as a local maximum for the evaluation range when the maximum is greater than the points; and
determining that the maximum is not the local maximum when the maximum is less than at least one of the points in the evaluation range.
10. The method of claim 9, further comprising:
de-identifying a maximum identified as a local maximum when the maxima are closer together than a predetermined remove maximum threshold; and
adding a maximum to the local maxima when the maxima are farther apart than a predetermined add maximum threshold.
11. A method, comprising:
mapping a first set of motion phases to a descending amplitude region of at least one motion cycle of a motion signal including a plurality of motion cycles, and the descending amplitude region includes the signal between the lesser of the cycle maximum and a mean signal maxima and a greater of a cycle minimum and a mean signal minima;
mapping a second set of motion phases to an ascending region of the at least one motion cycle, and the ascending region of the at least one motion cycle includes the signal between the greater of the cycle minimum and the mean signal minima and the lesser of the cycle maximum and the mean signal maxima; and
reconstructing data acquired from a scanner according to at least one of the first set of motion phases or the second set of motion phases.