Object-Tracking systems and methods
Systems and methods for tracking, identifying, labeling and/or classifying objects or features of interest, such as follicular units are provided. In some embodiments the identified and labeled features of interest, such as follicular units, may be used for planning hair harvesting, hair implantation and/or performing hair transplantation procedures.
1. A method for labeling hair for use in hair transplantation procedure, the method comprising:
obtaining an image of a region of interest;
identifying follicular units in the region of interest, including their location and orientation;
classifying the follicular units in the region of interest into follicular unit classes based on a number of hairs in the respective follicular units, wherein the follicular unit classes represent the number of hairs in each respective follicular unit;
labeling and recording the follicular units according to their location and classification; and
using the follicular units labeling for planning hair transplantation, or real-time harvesting, including determining which follicular units to harvest from the region of interest based on the follicular unit classes of the follicular units in the region of interest.
2. The method of claim 1 , wherein identifying follicular units comprises identifying one or more characteristics from a following list: color, length, type, shape, and emergence angle.
3. The method of claim 1 , further comprising counting the follicular units in the region of interest.
4. The method of claim 1 , further comprising determining how many follicular units per cm 2 to extract from the region of interest based on the classification and a desired density in an implanting area.
5. The method of claim 1 , further comprising analyzing the follicular units to determine a follicular unit density, baldness pattern, or other criteria for implanting follicular units.
6. The method of claim 1 , comprising obtaining the image with an image acquisition device and transmitting the obtained image to an image processor.
7. The method of claim 6 , wherein the image processor generates a hair implantation plan based on information in the image, and wherein the image processor is operatively connected to a robotic hair transplantation system that is configured and programmed to implement the plan.
8. The method of claim 1 , comprising identifying one or more marker in the image, and wherein identifying the one or more marker comprises analyzing at least one of a length, an area, a shape, a type, or a color of the at least one marker.
9. The method of claim 8 , wherein the one or more marker is a follicular unit and identifying the at least one marker further comprises analyzing at least one of the emergence angle of the follicular unit from the body surface and a caliber of the hair.
10. The method of claim 1 , further comprising utilizing a clustering algorithm to locate any bald spots in the image, and generating implantation sites located within the bald spots.
11. A system for labeling hair, the system comprising:
an interface configured to receive image data corresponding to a region of interest containing follicular units;
an image processor comprising one or more modules for executing operations on the image data, the one or more modules including instructions for:
identifying follicular units in the region of interest, including their location and orientation;
classifying the follicular units in the region of interest into follicular unit classes based on a number of hairs in the respective follicular units, wherein the follicular unit classes represent the number of hairs in each respective follicular unit;
labeling and recording the follicular units according to their location and classification; and
using the labeled follicular units to plan hair transplantation, or real time harvesting, including determining which follicular units to harvest from the region of interest based on the follicular unit classes of the follicular units in the region of interest.
12. The system of claim 11 , further comprising an image acquisition device, the image acquisition device providing image of a video feed, photographs, or other representation of the region of interest.
13. The system of claim 11 , wherein the image processor is operatively connected to a robotic hair transplantation system configured to implement the planned hair transplantation or the real-time harvesting.
14. The system of claim 11 , wherein the one or more modules includes instructions for determining a follicular unit density, baldness pattern, or other criteria for implanting follicular units.
15. The system of claim 11 , wherein the follicular units are sorted according to selected criteria, and the image processor is configured to select a particular follicular unit to be harvested based on the selected criteria.
16. The system of claim 11 , wherein the system comprises an implantation planning system and the region of interest comprises a recipient area, and
wherein the one or more modules includes instructions for locating a bald spot within the recipient area using a clustering algorithm and generating implantation sites within the bald spot.
17. The system of claim 11 , the system further comprising:
a marker referencing system configured to detect at least one marker, determine a frame of reference corresponding to the at least one marker, and adjust the frame of reference corresponding to a change in position of the at least one marker.
18. The system of claim 17 , wherein the image processor is further configured to define a frame of reference based on a pixel intensity data, without any a priori knowledge of the follicular unit locations.
19. The system of claim 11 , wherein the system further comprises image stabilization algorithms configured to substantially reduce a chance of mis-labeling the follicular units.
20. A system for labeling hair, the system comprising:
an interface configured to receive image data corresponding to a region of interest containing follicular units;
an image processor comprising one or more modules for executing operations on the image data, the one or more modules including instructions for:
identifying follicular units in the region of interest, including their location and orientation;
classifying the follicular units in the region of interest based on a number of hairs in the respective follicular units;
labeling and recording the follicular units according to their location and classification; and
using the labeled follicular units to plan hair transplantation, or real time harvesting and/or implantation;
the system further comprising:
a marker referencing system configured to detect at least one marker, determine a frame of reference corresponding to the at least one marker, and adjust the frame of reference corresponding to a change in position of the at least one marker;
wherein the image processor is further configured to define a frame of reference based on a pixel intensity data, without any a priori knowledge of the follicular unit locations.