Apparatus and methods of automated tracking and counting of objects on a resource-constrained device

1. An automated object tracking and counting system, comprising:

a memory comprising instructions; and

a processor in communication with the memory and configured to execute the instructions, wherein the processor is configured to:

obtain a set of image frames captured over time;

detect one or more objects in the set of image frames;

track positioning of the detected one or more objects in each of the set of image frames;

determine whether a current timing condition meets one or more classification timing rules;

select a subset of image frames from the set of image frames based on a selection parameter of each of the subset of image frames meeting a selection criteria, in response to the current timing condition meeting the one or more classification timing rules, wherein the selection parameter includes a distance of a position of each of the subset of image frames to a target position of a target image frame, and wherein the selection criteria comprises a number of image frames having a lowest distance to the target position of the target image frame;

classify as a respective object type each of the detected one or more objects;

count a number of the classified object types in the subset of image frames; and

output the number of the classified object types as a current count of the classified object type.

2. The system of claim 1 , wherein the selection parameter includes an amount that each of the subset of image frames covers a target image frame, and wherein the selection criteria comprises a number of image frames having a highest amount of coverage.

3. The system of claim 1 , wherein the selection parameter includes a direction of movement of each of the subset of image frames, and wherein the selection criteria comprises a defined direction of movement.

4. The system of claim 1 , wherein the one or more classification timing rules allow for adjustability in balancing classification quality and processing speed.

5. The system of claim 1 , wherein the one or more classification timing rules include enabling the processor to perform one or more of the selecting, the classifying, or the counting:

only when the detecting or the tracking is not operating;

when a number of the subset of image frames or a memory size of the number of the subset of image frames are pending processing; or

when at least one of the subset of image frames is pending processing and a time since a last one of the selecting, the classifying, or the counting was performed satisfies a threshold.

6. The system of claim 1 , wherein the processor is further configured to add the current count corresponding to the number of the classified object types to a value of a previous total count of the classified object types to define a current total count, and to output the current total count.

7. The system of claim 1 , wherein the processor is further configured to:

obtain another set of image frames captured over time in response to the current timing condition not meeting the one or more classification timing rules; and

perform the detecting and tracking for the another set of image frames.

8. An automated method of counting objects, comprising:

receiving a plurality of image frames from a camera;

detecting at least a first unidentified object in each of a first set of the plurality of image frames;

tracking at least the first unidentified object through the first set of the plurality of image frames;

determining a selection parameter associated with each of the first set of the plurality of image frames;

selecting a subset of image frames from the first set of the plurality of image frames based on each selection parameter of the subset of image frames meeting a selection criteria, wherein each selection parameter includes a distance of a position of each of the subset of image frames to a target position of a target image frame, and wherein the selection criteria comprises a number of image frames having a lowest distance to the target position of the target image frame;

determining that a classification timing trigger meets a trigger condition;

automatically classifying at least the first unidentified object as a first type of object based on analyzing the subset of image frames in response to the classification timing trigger meeting the trigger condition;

identifying a number of the first type of object in the subset of image frames to define a current count;

updating a total count of the first type of object based on the number of the first type of object defined by the current count; and

outputting the current count and/or the total count of the first type of object.

9. The method of claim 8 , wherein the selection parameter includes an amount that each of the subset of image frames covers a target image frame, and wherein the selection criteria comprises a number of image frames having a highest amount of coverage.

10. The method of claim 8 , wherein the selection parameter includes a direction of movement of each of the subset of image frames, and wherein the selection criteria comprises a defined direction of movement.

11. The method of claim 8 , wherein the trigger condition allows for adjustability in balancing classification quality and processing speed.

12. The method of claim 8 , wherein the trigger condition includes enabling the method to perform one or more of the selecting, the classifying, or the counting:

only when the detecting or the tracking is not operating;

when a number of the subset of image frames or a memory size of the number of the subset of image frames are pending processing; or

when at least one of the subset of image frames is pending processing and a time since a last one of the selecting, the classifying, or the counting was performed satisfies a threshold.

13. The method of claim 8 , further comprising adding the current count corresponding to the number of the classified object types to a value of a previous total count of the classified object types to define a current total count, and to output the current total count.

14. The method of claim 8 , further comprising:

obtaining another set of image frames captured over time in response to the classification timing trigger not meeting the trigger condition; and

performing the detecting and tracking for the another set of image frames.

15. A non-transitory computer-readable medium storing instructions for automated object tracking and counting that are executable by a processor, comprising:

instructions to cause the processor to obtain a set of image frames captured over time;

instructions to cause the processor to detect one or more objects in the set of image frames;

instructions to cause the processor to track positioning of the detected one or more objects in each of the set of image frames;

instructions to cause the processor to determine whether a current timing condition meets one or more classification timing rules;

instructions to cause the processor to select a subset of image frames from the set of image frames based on a selection parameter of each of the subset of image frames meeting a selection criteria, in response to the current timing condition meeting the one or more classification timing rules, wherein the selection parameter includes a distance of a position of each of the subset of image frames to a target position of a target image frame, and wherein the selection criteria comprises a number of image frames having a lowest distance to the target position of the target image frame;

instructions to cause the processor to classify as a respective object type each of the detected one or more objects;

instructions to cause the processor to count a number of the classified object types in the subset of image frames; and

instructions to cause the processor to output the number of the classified object types as a current count of the classified object type.

16. The non-transitory computer-readable medium of claim 15 , wherein the one or more classification timing rules allow for adjustability in balancing classification quality and processing speed.

17. The non-transitory computer-readable medium of claim 15 , wherein the one or more classification timing rules include enabling the processor to perform one or more of the selecting, the classifying, or the counting:

only when the detecting or the tracking is not operating;

when a number of the subsets of image frames or a memory size of the number of the subsets of image frames are pending processing; or

when at least one of the subset of image frames is pending processing and a time since a last one of the selecting, the classifying, or the counting was performed satisfies a threshold.