Abstract: Various systems and methods that enhance an exercise or other physical activity performed by a user are described. In some embodiments, a classification system communicates with a media hub to receive images and perform various methods for classifying or detecting poses, exercises, and/or movements performed by a user during an activity. In some embodiments, the systems and methods include a movements database (dB) that stores information as entries relating individual movements to data associated with the individual movements. Various systems, including class generation systems and body focus/activity systems, can utilize the movements database when presenting class content to users and/or presenting exercise information (e.g., muscle groups worked or targeted) to the users.

Abstract: A user-friendly and interactively created multimedia electronic message, as well as a system and method for creating such messages, combines an audio component (e.g. a voice-over, music, etc.) with user-interaction events that act upon selected visual media that serve as a visual background to the message. The visual media can be images, sequences of images, video, files such as documents or simply a pre-established library of background templates. The user interaction events can be sketch animations, text animations, symbols, shapes, emoticons and image transformation (e.g. pan, zoom, rotation, etc.) events. The user-interaction events may be time-correlated with the audio component through a common clock that is initiated by, and runs throughout, the audio recordation process, or they may be added outside of the audio component time-line.

Abstract: A method and system for probe-based pattern matching including an apparatus for synthetic training of a model of a pattern. The apparatus comprises a sensor for obtaining an image of the pattern and a processor for receiving the image of the pattern from the sensor and running a program. In the steps performed by the program a boundary of the pattern in the image is identified. A plurality of positive probes are placed at selected points along the boundary of the pattern and at least one straight segment of the boundary of the pattern is identified. The at least one straight segment of the boundary is extended to provide an imaginary straight segment and a plurality of negative probes are placed at selected points along the imaginary straight segment, where each negative probe has a negative weight.

Abstract: A method and system for probe-based pattern matching including an apparatus for synthetic training of a model of a pattern. The apparatus comprises a sensor for obtaining an image of the pattern and a processor for receiving the image of the pattern from the sensor and running a program. In the steps performed by the program a boundary of the pattern in the image is identified. A plurality of positive probes are placed at selected points along the boundary of the pattern and at least one straight segment of the boundary of the pattern is identified. The at least one straight segment of the boundary is extended to provide an imaginary straight segment and a plurality of negative probes are placed at selected points along the imaginary straight segment, where each negative probe has a negative weight.

Abstract: A method for detecting moving objects including people. Enhanced monitoring, safety and security is provided through the use of a monocular camera and a structured light source, by trajectory computation, velocity computation, or counting of people and other objects passing through a laser plane arranged perpendicular to the ground, and which can be setup anywhere near a portal, a hallway or other open area. Enhanced security is provided for portals such as revolving doors, mantraps, swing doors, sliding doors, etc., using the monocular camera and structured light source to detect and, optionally, prevent access violations such as “piggybacking” and “tailgating”.

Abstract: A Skqueak™ is an interactively created electronic memo/message that combines a voiceover with user-interaction elements on a selected background. The background could be images, sequence of images from a video, entire video, files such as documents or pre-canned templates. The user inter-action elements are sketch animations, text animations, symbols, shapes, emoticons, image transformation events (pan, zoom, rotation etc.). Skqueak™ also denotes the application that allows the creation of a Skqueak™. Skqueak™ also represents a web service available at www.skqueak.com that allows the creation, viewing, storing, sharing, searching, annotating, and manipulation of Skqueaks.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: A system and method of auto-exposure control is provided for image acquisition hardware using three dimensional information to identify a region(s) of interest within an acquired 2D image or images upon which to apply traditional auto-exposure techniques. By performing auto-exposure analysis over the region of interest, the acquisition property settings can be assigned such that the light levels within the region of interest fall within the linear range, producing sufficient grayscale information for identifying particular objects and profiles in subsequently acquired images. For example, in a machine vision application that detects people passing through a doorway, the region of interest can be the portion of the 2D image that generated 3D features of a head and shoulders profile within a 3D model of the doorway scene. With higher quality images, more accurate detection of people candidates within the monitored scene results.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: This invention provides a system and method for object detection and collision avoidance for objects and vehicles located behind the cab or front section of an elongated, and possibly tandem, vehicle. Through the use of narrow-baseline stereo vision that can be vertically oriented relative to the ground/road surface, the system and method can employ relatively inexpensive cameras, in a stereo relationship, on a low-profile mounting, to perform reliable detection with good range discrimination. The field of detection is sufficiently behind and aside the rear area to assure an adequate safety zone in most instances. Moreover, this system and method allows all equipment to be maintained on the cab of a tandem vehicle, rather than the interchangeable, and more-prone-to-damage cargo section and/or trailer. One or more cameras can be mounted on, or within, the mirror on each side, on aerodynamic fairings or other exposed locations of the vehicle.

Abstract: A method, computer program product, and machine vision system for monitoring an activity area proximate an actuated passageway for the occurrence of an object-related event. The activity area includes a first activity zone and at least a second activity zone. The first and the at least a second activity zones are essentially parallel to the activity area. The actuated passageway is actuatable with a control signal. The occurrence of an object-related event is detected within the activity area. If the object-related event occurs within the first activity zone, a first algorithm is executed to generate the control signal. If the object-related event occurs within the at least a second activity zone, a second algorithm is executed to generate the control signal.

Abstract: A three-dimensional (3-D) machine-vision involving a method and apparatus for performing segmentation of 3-D objects. Multiple stereo-related sets (left/right, top/left, top/right) of two-dimensional video pixel data are separately processed into sets of edges. Each stereo-related set is then pair-wise processed to convert pairs of sets of edge data into 3-D point data. Multiple sets of pair-wise 3-D data are then merged and used for obtaining 3-D features which are then clustered into discrete 3-D objects that can lie on any arbitrary plane.

Abstract: Enhanced portal security is provided through stereoscopy, including a stereo door sensor for detecting and optionally preventing access violations, such as piggybacking and tailgating. A portal security system can include a 3D imaging system that generates a target volume from plural 2D images of a field of view about a portal; and a processor that detects and tracks people candidates moving through the target volume to detect a portal access event.