摘要:
A method for providing hand segmentation for gesture analysis may include determining a target region based at least in part on depth range data corresponding to an intensity image. The intensity image may include data descriptive of a hand. The method may further include determining a point of interest of a hand portion of the target region, determining a shape corresponding to a palm region of the hand, and removing a selected portion of the target region to identify a portion of the target region corresponding to the hand. An apparatus and computer program product corresponding to the method are also provided.
摘要:
A method for providing hand segmentation for gesture analysis may include determining a target region based at least in part on depth range data corresponding to an intensity image. The intensity image may include data descriptive of a hand. The method may further include determining a point of interest of a hand portion of the target region, determining a shape corresponding to a palm region of the hand, and removing a selected portion of the target region to identify a portion of the target region corresponding to the hand. An apparatus and computer program product corresponding to the method are also provided.
摘要:
A method for providing adaptive gesture analysis may include dividing a distance range into a plurality of depth ranges, generating a plurality of intensity images for at least two image frames, each of the intensity images providing image data indicative of a presence of objects at a corresponding depth range for a respective image frame, determining motion variation between the two image frames for each corresponding depth range, and determining depth of a target based at least in part on the motion variation. An apparatus and computer program product corresponding to the method are also provided.
摘要:
A method for providing adaptive gesture analysis may include dividing a distance range into a plurality of depth ranges, generating a plurality of intensity images for at least two image frames, each of the intensity images providing image data indicative of a presence of objects at a corresponding depth range for a respective image frame, determining motion variation between the two image frames for each corresponding depth range, and determining depth of a target based at least in part on the motion variation. An apparatus and computer program product corresponding to the method are also provided.
摘要:
Embodiments are directed to creating a triangle mesh by using a distance-minimum criterion on a plurality of feature points detected from an image, computing, based on the triangle mesh, global features that describe a global representation of content of the image, and computing, based on the triangle mesh, local features that describe a local representation of content of the image. The global features may include a triangle distribution scatter of mesh that shows a texture density of the content of the image and a color histogram of mesh region that represents image color information corresponding to a mesh region of interest. The local features may include a definition of each mesh triangle shape via its three angles and a color histogram of each mesh triangle to represent image color information corresponding to each triangle region.
摘要:
A computer interface may use touch- and non-touch-based gesture detection systems to detect touch and non-touch gestures on a computing device. The systems may each capture an image, and interpret the image as corresponding to a predetermined gesture. The systems may also generate similarity values to indicate the strength of a match between a captured image and corresponding gesture, and the system may combine gesture identifications from both touch- and non-touch-based gesture identification systems to ultimately determine the gesture. A threshold comparison algorithm may be used to apply different thresholds for different gesture detection systems and gesture types.
摘要:
A computer interface may use touch- and non-touch-based gesture detection systems to detect touch and non-touch gestures on a computing device. The systems may each capture an image, and interpret the image as corresponding to a predetermined gesture. The systems may also generate similarity values to indicate the strength of a match between a captured image and corresponding gesture, and the system may combine gesture identifications from both touch- and non-touch-based gesture identification systems to ultimately determine the gesture. A threshold comparison algorithm may be used to apply different thresholds for different gesture detection systems and gesture types.