Abstract: A method and apparatus to analyze video data comprising: using a camera with a computing device with a memory storage and a power source to capture and to store the video data; simultaneously compressing and analyzing said video data using Low Level Analysis of contours of static and moving objects within the video data; said compression can be wavelet-based decomposition; and said analysis of the video data compares real-time semantic human activity within the video data, whereby the method identifies the specific human activity within the video data; the camera can be wirelessly connected to a base station and communicates through 2-way full duplex connection.

Abstract: A method and apparatus for scalable symmetric data compression and decompression (codec), optimized for real-time processing of high-resolution continuous-tone 2D input, such as video and images. Following a dyadic n-level DWT decomposition of input, the coding of subbands is spatially partitioned to enable strong parallelism that maps into concurrent encoding threads, based on typical artifacts of H-bands on initial levels—large areas of contiguous zeros interspersed with sparse and highly redundant non-zero values. Variable length codewords of both non-zero values and their positions are mapped into a linear bitstream by a combined limited sequential and parallel procedure of at most log2 n iterations, with both lossless and lossy variants enabled. The compressed bitstream of self-delimiting entries is decoded in a symmetric iterative procedure that delivers to decoding threads the non-zero values and position codewords for final image restoration.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user-initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user-initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.

Abstract: A technique for analyzing and interpreting user inputs to a computer, such as strokes, key depressions, or voice signals to a hand-held, pen-based computer system. Inputs to the system are received at a user interface, such as a dual function display/input screen from users in the form of pen strokes or gestures. A database stores the input data strokes and hypotheses regarding possible interpretations of the strokes. Recognition of the input strokes and recognition of higher level combinations of strokes (forming characters and words, etc.) is performed using recognizers, or recognition domains, each of which performs a particular recognition task. A controller is provided for controlling the hypotheses database and for scheduling the recognition tasks in the recognition domains. Arbitration resolves conflicts among competing hypotheses associated with each interpretation. The recognition domains, or recognizers generate two or more competing interpretations for the same input.

Abstract: An apparatus for recognizing shapes characterized by a stroke grouper receptive to a plurality of strokes formed on a screen of a pen-based computer system; a shape recognition engine receptive to a stroke group produced by the stroke grouper; and a knowledge base coupled to the shape recognition engine, where the knowledge base includes, at a minimum, knowledge concerning closed polygons and closed curves. Preferably, the closed curves of the knowledge base include both circles and ellipses. A method for recognizing digitized shapes in a computer system includes the steps of receiving at least one user-initiated stroke; grouping the user-initiated stroke with related strokes to form a stroke group; and analyzing the stroke group to make a best-guess shape represented by the stroke group. Preferably, the method also looks for other shapes which are related to the best-guess shape and modifying at least one of the location, size, or shape of the best-guess shape to conform with the other shapes.