Abstract: A method for analyzing time series data to identify an event of interest is provided. The method includes receiving, at a computing device, time series data that includes the event of interest, identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the time series data, and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.

Abstract: A method for analyzing time series data to identify an event of interest is provided. The method includes receiving, at a computing device, time series data that includes the event of interest, identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the time series data, and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.

Abstract: A method for analyzing time series data to identify an event of interest is provided. The method includes receiving, at a computing device, time series data that includes the event of interest, identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the time series data, and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.

Abstract: A method for analyzing time series data to identify an event of interest is provided. The method includes receiving, at a computing device, time series data that includes the event of interest, identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the time series data, and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.

Abstract: A method and system for compressing and displaying a digital ink trace. Raw ink data is smoothed, and sharp points of the smoothed line are found. Curve-fitting is then used to generate a mathematical expression that defines the line segments between adjacent sharp points. The ink trace then is represented by a backbone spline that includes the sharp points and the mathematical expressions for the line segments. Thickness information, such as pressure or acceleration information, is combined with the backbone spline to provide a compressed ink file that represents a contour curve of the original ink trace. A display module uses an algorithm to separate the contour curve into a sequence of straight lines. A set of pixels is then generated for the display of each straight line using a novel antialiasing method. The pixels at the ends of adjacent straight lines are aligned using a weighting algorithm.

Abstract: A system for separating text and drawings in a digital ink file (e.g., a handwritten digital ink file). A stroke analyzer classifies single strokes that have been input by a user as “text” or “unknown.” The stroke analyzer utilizes a trainable classifier, such as a support vector machine. A grouping component is provided that groups text strokes in an attempt to form text objects (e.g., words, characters, or letters). The grouping component also groups unknown strokes in an attempt to form objects (e.g., shapes, drawings, or even text). A trainable classifier, such as a support vector machine, evaluates the grouped strokes to determine if they are objects.

Abstract: A method and system for compressing and displaying a digital ink trace. Raw ink data is smoothed, and sharp points of the smoothed line are found. Curve-fitting is then used to generate a mathematical expression that defines the line segments between adjacent sharp points. The ink trace then is represented by a backbone spline that includes the sharp points and the mathematical expressions for the line segments. Thickness information, such as pressure or acceleration information, is combined with the backbone spline to provide a compressed ink file that represents a contour curve of the original ink trace. A display module uses an algorithm to separate the contour curve into a sequence of straight lines. A set of pixels is then generated for the display of each straight line using a novel antialiasing method. The pixels at the ends of adjacent straight lines are aligned using a weighting algorithm.

Abstract: A method and system for compressing and displaying a digital ink trace. Raw ink data is smoothed, and sharp points of the smoothed line are found. Curve-fitting is then used to generate a mathematical expression that defines the line segments between adjacent sharp points. The ink trace then is represented by a backbone spline that includes the sharp points and the mathematical expressions for the line segments. Thickness information, such as pressure or acceleration information, is combined with the backbone spline to provide a compressed ink file that represents a contour curve of the original ink trace. A display module uses an algorithm to separate the contour curve into a sequence of straight lines. A set of pixels is then generated for the display of each straight line using a novel antialiasing method. The pixels at the ends of adjacent straight lines are aligned using a weighting algorithm.

Abstract: A method and system for compressing and displaying a digital ink trace. Raw ink data is smoothed, and sharp points of the smoothed line are found. Curve-fitting is then used to generate a mathematical expression that defines the line segments between adjacent sharp points. The ink trace then is represented by a backbone spline that includes the sharp points and the mathematical expressions for the line segments. Thickness information, such as pressure or acceleration information, is combined with the backbone spline to provide a compressed ink file that represents a contour curve of the original ink trace. A display module uses an algorithm to separate the contour curve into a sequence of straight lines. A set of pixels is then generated for the display of each straight line using a novel antialiasing method. The pixels at the ends of adjacent straight lines are aligned using a weighting algorithm.

Abstract: A system for separating text and drawings in a digital ink file (e.g., a handwritten digital ink file). A stroke analyzer classifies single strokes that have been input by a user as “text” or “unknown.” The stroke analyzer utilizes a trainable classifier, such as a support vector machine. A grouping component is provided that groups text strokes in an attempt to form text objects (e.g., words, characters, or letters). The grouping component also groups unknown strokes in an attempt to form objects (e.g., shapes, drawings, or even text). A trainable classifier, such as a support vector machine, evaluates the grouped strokes to determine if they are objects.