Dynamic learning for object tracking
First Claim
1. A method for tracking an object, comprising:
- detecting a plurality of objects from image data, wherein the plurality of objects comprises a first object, and wherein the first object is identified using a first label for a positive tracking object and remaining objects of the plurality of objects are identified using a second label for negative tracking objects to indicate that the first object is to be the focus of tracking and that the remaining objects are not to be the focus of tracking, and to indicate that information associated with the first object is maintained in a dataset different than information associated with the remaining objects of the plurality of objects;
tracking a difference associated with one or more features for the plurality of objects with respect to the first object from the image data, wherein tracking the difference associated with the one or more features for the plurality of objects comprises dynamically learning and storing information about the difference of the one or more features associated with one or more of the plurality of objects, and wherein the dynamically learned information is maintained in an IDFL (Interactive Decision Forest Learning) dataset for each detected object; and
identifying the first object from the plurality of objects using the tracking difference associated with the one or more features for the plurality of objects.
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Abstract
Techniques described herein relate to mobile computing device technologies, such as systems, methods, apparatuses, and computer-readable media for tracking an object from a plurality of objects. In one aspect, the plurality of objects may be similar. Techniques discussed herein propose dynamically learning information associated with each of the objects and discriminating between objects based on their differentiating features. In one implementation, this may be done by maintaining a database associated with each object and updating the dynamic database transferred while the objects are tracked. The tracker uses algorithmic means for differentiating objects by focusing on the differences amongst the objects. For example, in one implementation, the method may weigh the differences between different fingers higher than their associated similarities to facilitate differentiating the fingers.
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Citations
38 Claims
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1. A method for tracking an object, comprising:
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detecting a plurality of objects from image data, wherein the plurality of objects comprises a first object, and wherein the first object is identified using a first label for a positive tracking object and remaining objects of the plurality of objects are identified using a second label for negative tracking objects to indicate that the first object is to be the focus of tracking and that the remaining objects are not to be the focus of tracking, and to indicate that information associated with the first object is maintained in a dataset different than information associated with the remaining objects of the plurality of objects; tracking a difference associated with one or more features for the plurality of objects with respect to the first object from the image data, wherein tracking the difference associated with the one or more features for the plurality of objects comprises dynamically learning and storing information about the difference of the one or more features associated with one or more of the plurality of objects, and wherein the dynamically learned information is maintained in an IDFL (Interactive Decision Forest Learning) dataset for each detected object; and identifying the first object from the plurality of objects using the tracking difference associated with the one or more features for the plurality of objects. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computing device, comprising:
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a camera coupled to the computing device for acquiring an image; a processor configured to; detect a plurality of objects from image data from the image, wherein the plurality of objects comprises a first object, and wherein the first object is identified using a first label for a positive tracking object and remaining objects of the plurality of objects are identified using a second label for negative tracking objects to indicate that the first object is to be the focus of tracking and that the remaining objects are not to be the focus of tracking, and to indicate that information associated with the first object is maintained in a dataset different than information associated with the remaining objects of the plurality of objects; and a tracking module executing on the processor configured to; track a difference associated with one or more features for the plurality of objects with respect to the first object from the image data; and identify the first object from the plurality of objects using the tracking difference associated with the one or more features for the plurality of objects. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium comprises instructions executable by a processor, the instructions comprising instructions to:
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detect a plurality of objects from image data, wherein the plurality of objects comprises a first object, and wherein the first object is identified using a first label for a positive tracking object and remaining objects of the plurality of objects are identified using a second label for negative tracking objects to indicate that the first object is to be the focus of tracking and that the remaining objects are not to be the focus of tracking, and to indicate that information associated with the first object is maintained in a dataset different than information associated with the remaining objects of the plurality of objects; track a difference associated with one or more features for the plurality of objects with respect to the first object from the image data; and identify the first object from the plurality of objects using the tracking difference associated with the one or more features for the plurality of objects. - View Dependent Claims (26, 27, 28, 29, 30, 31)
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32. An apparatus, comprising:
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means for detecting a plurality of objects from image data, wherein the plurality of objects comprises a first object, and wherein the first object is identified using a first label for a positive tracking object and remaining objects of the plurality of objects are identified using a second label for negative tracking objects to indicate that the first object is to be the focus of tracking and that the remaining objects are not to be the focus of tracking, and to indicate that information associated with the first object is maintained in a dataset different than information associated with the remaining objects of the plurality of objects; means for tracking a difference associated with one or more features for the plurality of objects with respect to the first object from the image data; and means for identifying the first object from the plurality of objects using the tracking difference associated with the one or more features for the plurality of objects. - View Dependent Claims (33, 34, 35, 36, 37, 38)
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Specification