Recognizing hand poses and/or object classes
First Claim
1. One or more computer-readable storage devices to store processor executable instructions that, when the instructions are implemented by one or more processors, configure the one or more processors to implement a method comprising:
- receiving at least one image of an item to be classified as one of a plurality of specified classes, those classes comprising hand pose classes and object classes;
accessing a plurality of decision trees which have been formed in a training process using information at least about classification accuracy;
classifying the image, using the one or more processors, into one of the classes using a unified recognition process at least by applying the plurality of decision trees to at least part of the image, the unified recognition process based in part on the plurality of decision trees being applied by a single module and are used to recognize hand poses, objects, and touch/no touch user interactions; and
storing the classified image in memory.
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Accused Products
Abstract
There is a need to provide simple, accurate, fast and computationally inexpensive methods of object and hand pose recognition for many applications. For example, to enable a user to make use of his or her hands to drive an application either displayed on a tablet screen or projected onto a table top. There is also a need to be able to discriminate accurately between events when a user'"'"'s hand or digit touches such a display from events when a user'"'"'s hand or digit hovers just above that display. A random decision forest is trained to enable recognition of hand poses and objects and optionally also whether those hand poses are touching or not touching a display surface. The random decision forest uses image features such as appearance, shape and optionally stereo image features. In some cases, the training process is cost aware. The resulting recognition system is operable in real-time.
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Citations
7 Claims
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1. One or more computer-readable storage devices to store processor executable instructions that, when the instructions are implemented by one or more processors, configure the one or more processors to implement a method comprising:
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receiving at least one image of an item to be classified as one of a plurality of specified classes, those classes comprising hand pose classes and object classes; accessing a plurality of decision trees which have been formed in a training process using information at least about classification accuracy; classifying the image, using the one or more processors, into one of the classes using a unified recognition process at least by applying the plurality of decision trees to at least part of the image, the unified recognition process based in part on the plurality of decision trees being applied by a single module and are used to recognize hand poses, objects, and touch/no touch user interactions; and storing the classified image in memory. - View Dependent Claims (2, 3, 4, 5)
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6. An apparatus comprising:
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an input arranged to receive at least one image of an item to be classified as one of a plurality of specified classes; a memory arranged to store a plurality of decision trees which have been formed in a training process using information about classification accuracy and information about computational cost; and a processor arranged to; classify the image into one of the classes at least by applying the plurality of decision trees to a plurality of pixels of the image; record an outcome for each decision tree applied to the plurality of pixels, the outcome being an index of a leaf on the decision tree that is reached during the application of the decision tree to the image; compute a histogram for each decision tree based in part on the recorded outcomes; and store the classified image into memory. - View Dependent Claims (7)
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Specification