Abstract: A method, system and computer program for segmenting an image are provided. The system may include an image acquisition system for acquiring a plurality of images; and a processor for clustering pixels from one of the images into one or more segments, each segment being defined in a state of either stable, mesostable or unstable, the processor further performing the clustering by determining residual pixels changing by more than a predetermined threshold, grouping the determined residual pixels to form segments selected from the group of unstable and mesostable segments, determining depth for all unstable and mesostable segments, transitioning unstable segments to corresponding mesostable segments if the unstable segment is determined to have a valid depth, transitioning mesostable segments to corresponding stable segments upon a determination that one or more predetermined stability criteria have been met, and merging one or more stable and mesostable segments.

Abstract: A method and apparatus for segmenting an image are provided. The method may include the steps of clustering pixels from one of a plurality of images into one or more segments, determining one or more unstable segments changing by more than a predetermined threshold from a prior of the plurality of images, determining one or more segments transitioning from an unstable to a stable segment, determining depth for one or more of the one or more segments that have changed by more than the predetermined threshold, determining depth for one or more of the one or more transitioning segments, and combining the determined depth for the one or more unstable segments and the one or more transitioning segments with a predetermined depth of all segments changing less than the predetermined threshold from the prior of the plurality of images.

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

Abstract: A method, system and computer program for segmenting an image are provided. The method may include the steps of acquiring a plurality of images, and clustering pixels from one of the plurality of images into one or more segments, each segment being defined in a state of either stable, mesostable or unstable. The clustering may include the steps of determining residual pixels changing by more than a predetermined threshold, grouping the determined residual pixels to form segments selected from the group of unstable and mesostable segments, determining depth for all unstable and mesostable segments, transitioning unstable segments to corresponding mesostable segments if predetermined stability criteria are met, transitioning mesostable segments to corresponding stable segments upon a determination that the mesostable segments have remained stable for a predetermined number of frames, and merging stable and mesostable segments.

Abstract: A method and system for performing gesture recognition of a vehicle occupant employing a time of flight (TOF) sensor and a computing system in a vehicle. An embodiment of the method of the invention includes the steps of receiving one or more raw frames from the TOF sensor, performing clustering to locate one or more body part clusters of the vehicle occupant, calculating the location of the tip of the hand of the vehicle occupant, determining whether the hand has performed a dynamic or a static gesture, retrieving a command corresponding to one of the determined static or dynamic gestures, and executing the command.

Abstract: A method and system to determine the disparity associated with one or more textured regions of a plurality of images is presented. The method comprises the steps of breaking up the texture into its color primitives, further segmenting the textured object into any number of objects comprising such primitives, and then calculating a disparity of these objects. The textured objects emerge in the disparity domain, after having their disparity calculated. Accordingly, the method is further comprised of defining one or more textured regions in a first of a plurality of images, determining a corresponding one or more textured regions in a second of the plurality of images, segmenting the textured regions into their color primitives, and calculating a disparity between the first and second of the plurality of images in accordance with the segmented color primitives.

Abstract: A method and system for segmenting a plurality of images. The method comprises the steps of segmenting the image through a novel clustering technique that is, generating a composite depth map including temporally stable segments of the image as well as segments in subsequent images that have changed. These changes may be determined by determining one or more differences between the temporally stable depth map and segments included in one or more subsequent frames. Thereafter, the portions of the one or more subsequent frames that include segments including changes from their corresponding segments in the temporally stable depth map are processed and are combined with the segments from the temporally stable depth map to compute their associated disparities in one or more subsequent frames. The images may include a pair of stereo images acquired through a stereo camera system at a substantially similar time.

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

Abstract: A method and system for performing gesture recognition of a vehicle occupant employing a time of flight (TOF) sensor and a computing system in a vehicle. An embodiment of the method of the invention includes the steps of receiving one or more raw frames from the TOF sensor, performing clustering to locate one or more body part clusters of the vehicle occupant, calculating the location of the tip of the hand of the vehicle occupant, determining whether the hand has performed a dynamic or a static gesture, retrieving a command corresponding to one of the determined static or dynamic gestures, and executing the command.

Abstract: A method and system for generating a disparity map. The method comprises the steps of generating a first disparity map based upon a first image and a second image acquired at a first time, acquiring at least a third image and a fourth image at a second time, and determining one or more portions comprising a difference between one of the first and second images and a corresponding one of the third and fourth images. A disparity map update is generated for the one or more determined portions, and a disparity map is generated based upon the third image and the fourth image by combining the disparity map update and the first disparity map.

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

Abstract: A three-dimensional virtual-touch human-machine interface system (20) and a method (100) of operating the system (20) are presented. The system (20) incorporates a three-dimensional time-of-flight sensor (22), a three-dimensional autostereoscopic display (24), and a computer (26) coupled to the sensor (22) and the display (24). The sensor (22) detects a user object (40) within a three-dimensional sensor space (28). The display (24) displays an image (42) within a three-dimensional display space (32). The computer (26) maps a position of the user object (40) within an interactive volumetric field (36) mutually within the sensor space (28) and the display space (32), and determines when the positions of the user object (40) and the image (42) are substantially coincident. Upon detection of coincidence, the computer (26) executes a function programmed for the image (42).

Abstract: A method and system for performing gesture recognition of a vehicle occupant employing a time of flight (TOF) sensor and a computing system in a vehicle. An embodiment of the method of the invention includes the steps of receiving one or more raw frames from the TOF sensor, performing clustering to locate one or more body part clusters of the vehicle occupant, calculating the location of the tip of the hand of the vehicle occupant, determining whether the hand has performed a dynamic or a static gesture, retrieving a command corresponding to one of the determined static or dynamic gestures, and executing the command.

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

Abstract: Method, computer program and system for tracking movement of a subject. The method includes receiving data from a distributed network of camera sensors employing one or more emitted light sources associated with one or more of the one or more camera sensors to generate a volumetric three-dimensional representation of the subject, identifying a plurality of clusters within the volumetric three-dimensional representation that correspond to motion features indicative of movement of the motion features of the subject, presenting one or more objects on one or more three dimensional display screens, and using the plurality of fixed position sensors to track motion of the motion features of the subject and track manipulation of the motion features of the volumetric three-dimensional representation to determine interaction of one or more of the motion features of the subject and one or more of the one or more objects on the three dimensional display.

Abstract: Method, computer program and system for tracking movement of a subject. The method includes receiving data from a distributed network of camera sensors employing one or more emitted light sources associated with one or more of the one or more camera sensors to generate a volumetric three-dimensional representation of the subject, identifying a plurality of clusters within the volumetric three-dimensional representation that correspond to motion features indicative of movement of the motion features of the subject, presenting one or more objects on one or more three dimensional display screens, and using the plurality of fixed position sensors to track motion of the motion features of the subject and track manipulation of the motion features of the volumetric three-dimensional representation to determine interaction of one or more of the motion features of the subject and one or more of the one or more objects on the three dimensional display.

Abstract: A three-dimensional virtual-touch human-machine interface system (20) and a method (100) of operating the system (20) are presented. The system (20) incorporates a three-dimensional time-of-flight sensor (22), a three-dimensional autostereoscopic display (24), and a computer (26) coupled to the sensor (22) and the display (24). The sensor (22) detects a user object (40) within a three-dimensional sensor space (28). The display (24) displays an image (42) within a three-dimensional display space (32). The computer (26) maps a position of the user object (40) within an interactive volumetric field (36) mutually within the sensor space (28) and the display space (32), and determines when the positions of the user object (40) and the image (42) are substantially coincident. Upon detection of coincidence, the computer (26) executes a function programmed for the image (42).

Abstract: Method, computer program and system for tracking movement of a subject. The method includes receiving data from a distributed network of camera sensors employing one or more emitted light sources associated with one or more of the one or more camera sensors to generate a volumetric three-dimensional representation of the subject, identifying a plurality of clusters within the volumetric three-dimensional representation that correspond to motion features indicative of movement of the motion features of the subject, presenting one or more objects on one or more three dimensional display screens, and using the plurality of fixed position sensors to track motion of the motion features of the subject and track manipulation of the motion features of the volumetric three-dimensional representation to determine interaction of one or more of the motion features of the subject and one or more of the one or more objects on the three dimensional display.

Abstract: A method and system for performing gesture recognition of a vehicle occupant employing a time of flight (TOF) sensor and a computing system in a vehicle. An embodiment of the method of the invention includes the steps of receiving one or more raw frames from the TOF sensor, performing clustering to locate one or more body part clusters of the vehicle occupant, locating the palm cluster of the vehicle occupant, calculating the location of the tip of the hand of the vehicle occupant, determining whether the hand has performed a dynamic or a static gesture, retrieving a command corresponding to one of the determined static or dynamic gestures, and executing the command.

Abstract: Method, computer program and system for tracking movement of a subject. The method includes receiving data from a distributed network of camera sensors employing one or more emitted light sources associated with one or more of the one or more camera sensors to generate a volumetric three-dimensional representation of the subject, identifying a plurality of clusters within the volumetric three-dimensional representation that correspond to motion features indicative of movement of the motion features of the subject, presenting one or more objects on one or more three dimensional display screens, and using the plurality of fixed position sensors to track motion of the motion features of the subject and track manipulation of the motion features of the volumetric three-dimensional representation to determine interaction of one or more of the motion features of the subject and one or more of the one or more objects on the three dimensional display.