Abstract: A method and system for detecting a commercial transaction through physical interactions with products, the system comprising a frame that is placed within a product display unit. The frame includes a shelf, at least one camera, a weight sensor, and display screens. The system further comprises a computing device communicatively connected to the frame. The computing device is configured to detect physical interactions with items that are placed on the shelf based on data that is received from the at least one camera and the weight sensor. The computing device is further configured to determine a commercial transaction associated with physical interactions and transmit item and price data to the display screens based on machine learning of the physical interactions with items.

Abstract: A method and system for detecting a commercial transaction through physical interactions with items, the method comprising receiving data from a plurality of sensory modules associated with one or more shelves within a container, the plurality of sensory modules including a static cameras module, a weight sensors module, and a video cameras module, wherein the data includes physical activities corresponding to items on the smart shelves in a given session. The method further comprises resolving the data from the sensory modules using probabilistic reasoning and machine learning, determining a new container state after the given session based on the resolved data, and determining a final commercial transaction based on the new container state.

Abstract: A method and system for extracting motion and structure from a sequence of images stored on a computer system, the method comprises obtaining images including a set of three-dimensional (3D) points over a plurality of frames, determining an instantaneous motion of the set of 3D points by an angular velocity and a translation with respect to an axis of rotation, computing an optical flow using the instantaneous motion of the set of 3D points based on a projection of velocity of the set of 3D points, computing a depth of the set of 3D points from the optical flow, and determining an epipolar line in the images using the optical flow.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut. The minimum cut thus found is interpreted as the segmentation with desired property.

Abstract: A method and system for extracting motion and structure from a sequence of images stored on a computer system, the method comprises obtaining images including a set of three-dimensional (3D) points over a plurality of frames, determining an instantaneous motion of the set of 3D points by an angular velocity and a translation with respect to an axis of rotation, computing an optical flow using the instantaneous motion of the set of 3D points based on a projection of velocity of the set of 3D points, computing a depth of the set of 3D points from the optical flow, and determining an epipolar line in the images using the optical flow.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut. The minimum cut thus found is interpreted as the segmentation with desired property.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut. The minimum cut thus found is interpreted as the segmentation with desired property.

Abstract: A method for displaying visual information corresponding to at least one user can including receiving a selection of at least one attribute to be viewed, with a computer arrangement, tracking at least one user pose of the at least one user in real-time using a marker-less capture procedure to generate tracking information, matching the at least one user pose with at least one database pose provided in a database based on the tracking information, and displaying the at least one database pose in combination with the at least one attribute.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut. The minimum cut thus found is interpreted as the segmentation with desired property.

Abstract: A method is disclosed to digitize and recognize planar shapes that are present in images and are desired to be recognized and extracted. These planar shapes can represent maps in cartography, they can represent patterns from garment styles, they can represent projections of real objects into a 2D picture. The images are obtained from image scanning techniques including digital cameras. The invention includes an automatic mode and a user interface for the semi-automatic mode of operation. The method has been carried out for patterns that were drawn or plotted on papers (not cut out), representing garment styles, and is readily applicable to other applications such as maps in cartography, and more generally to recognition of 3D objects from 2D images.

Abstract: A process and system are provided for determining a most likely combination of characters. In particular, character data which includes information indicative of at least one handwritten character is obtained. The character data includes at least one set of segmentation points for the handwritten character. Then, a score can be provided for each particular character of a set of previously stored characters based on a comparison between the character data and the previously stored particular character. In addition, it is possible to compare visual aspects of the handwritten character to visual aspects of each of the previously stored characters for determining likely characters. Also, a Fisher Matching procedure can be used on the character data to ascertain the likely characters. A plurality of handwritten characters can include a first character that is connected to a second character of the handwritten characters via a ligature.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut. The minimum cut thus found is interpreted as the segmentation with desired property.

Abstract: A process and system are provided for determining a most likely combination of characters. In particular, character data which includes information indicative of at least one handwritten character is obtained. The character data includes at least one set of segmentation points for the handwritten character. Then, a score can be provided for each particular character of a set of previously stored characters based on a comparison between the character data and the previously stored particular character. In addition, it is possible to compare visual aspects of the handwritten character to visual aspects of each of the previously stored characters for determining likely characters. Also, a Fisher Matching procedure can be used on the character data to ascertain the likely characters. A plurality of handwritten characters can include a first character that is connected to a second character of the handwritten characters via a ligature.

Abstract: A method is disclosed to automatically segment 3D and higher-dimensional images into two subsets without user intervention, with no topological restriction on the solution, and in such a way that the solution is an optimal in a precisely defined optimization criterion, including an exactly defined degree of smoothness. A minimum-cut algorithm is used on a graph devised so that the optimization criterion translates into the minimization of the graph cut.

Abstract: A data image management system (DIMS) that includes a local data image manager (LDIM), a remote data image manager (RDIM), and a remote persistent storage device (RPSD). The LDIM communicates with the RDIM through a direct communication link or through a communication network. The RDIM can store data on and retrieve data from the RPSD. In an environment where an LDIM has been installed in a computer having a “local” persistent storage device (LPSD), the DIMS allows for the storing of the LPSD's data image on the RPSD, with the LPSD serving as a persistent, consistent cache of the data image. The data image stored on the RPSD is referred to as the “master data image” and the data image cached on the LPSD is referred to as the “local data image” or “cached data image.” The LDIM functions to intercept read/write requests that are intended to be received by the LPSD. The read/write requests specify an address of the LPSD.

Abstract: A data image management system (DIMS) that includes a local data image manager (LDIM), a remote data image manager (RDIM), and a remote persistent storage device (RPSD). The LDIM communicates with the RDIM through a direct communication link or through a communication network. The RDIM can store data on and retrieve data from the RPSD. In an environment where an LDIM has been installed in a computer having a “local” persistent storage device (LPSD), the DIMS allows for the storing of the LPSD's data image on the RPSD, with the LPSD serving as a persistent, consistent cache of the data image. The data image stored on the RPSD is referred to as the “master data image” and the data image cached on the LPSD is referred to as the “local data image” or “cached data image.” The LDIM functions to intercept read/write requests that are intended to be received by the LPSD. The read/write requests specify an address of the LPSD.

Abstract: A data image management system (DIMS) that includes a local data image manager (LDIM), a remote data image manager (RDIM), and a remote persistent storage device (RPSD). The LDIM communicates with the RDIM through a direct communication link or through a communication network. The RDIM can store data on and retrieve data from the RPSD. In an environment where an LDIM has been installed in a computer having a “local” persistent storage device (LPSD), the DIMS allows for the storing of the LPSD's data image on the RPSD, with the LPSD serving as a persistent, consistent cache of the data image. The data image stored on the RPSD is referred to as the “master data image” and the data image cached on the LPSD is referred to as the “local data image” or “cached data image.” The LDIM functions to intercept read/write requests that are intended to be received by the LPSD. The read/write requests specify an address of the LPSD.

Abstract: A technique of tracking an object of interest in a sequence of images using active polyline contours. An image processor converts a sequence of images into digital image data related to light intensity at the pixels of each image. A computer stores the digital image data and forms an initial polyline that substantially outlines an edge of the object in a first image. The computer forms input polylines for each of the subsequent images which substantially outline the edge in the corresponding images and are derived from the optimal polyline of each previous such image. The computer processes the digital image data, performing a graph exploration procedure that starts with the initial polyline in the first image and the input polylines in the subsequent images. The graph exploration procedure searches polylines in a predefined search space to find the corresponding optimal polylines.