Abstract: A computerized visualization method for illustrating multi-dimensional data, comprising: receiving a plurality of location data points, each location data point having a plurality of measured features; choosing at least one location dimension from received said plurality of dimensions; grouping said plurality of location data points into a plurality of location groups according to chosen said at least one location dimension; plotting, by a processor, said plurality of location groups as a plurality of flower charts, each said plurality of flower charts, having a plurality of pie sectors, illustrates remaining said plurality of measured features subsequent to said choosing at least one location dimension; and positioning each said plurality of flower charts, in a visual representation, according to chosen said plurality of location dimensions.

Abstract: Methods, system and computer program products for spatiotemporal encounters detection of a plurality of moving objects are disclosed. The method includes receiving a dataset of a plurality of objects moving in a domain, structuring the dataset in a data structure to detect a plurality of spatiotemporal encounters among the plurality of objects, outputting a list of the detected spatiotemporal encounters. The plurality of spatiotemporal encounters may be detected in a single sweep over the received dataset.

Abstract: A computerized method for generating monitoring rules, comprising: presenting to a user a spatio-temporal data indicative of a plurality of spatio-temporal attributes of a plurality of image objects in a space during a period; selecting, by a user, at least one of a spatial pattern and a temporal pattern represented in said spatio-temporal data; analyzing said at least one of a spatial pattern and a temporal pattern to identify at least one of a spatial related characteristic of at least some of said plurality of image objects and a temporal related characteristic of at least some of said plurality of image objects; automatically generating at least one monitoring rule to track an occurrence of said at least one of a location related characteristic and a temporal related characteristic.

Abstract: Techniques are described for visualizing the mood of a group of individuals. In one example, a graphical display is divided into regions representing different emotions. Input indicative of an emotion is received from individuals located in an area of interest. As the input is received, a set of indicators is output in each of the regions of the graphical display. Each indicator represents a different one of the individuals who is experiencing the emotion associated with the region in which the indicator is displayed and is displayed with a color assigned to the emotion. The indicators are animated to move over time toward a center of the graphical display and are removed upon reaching the center of the graphical display. In this way, the graphical display depicts a current mood for the group and indicates a rate of change of each of the different emotions.

Abstract: Techniques are described for visualizing the mood of a group of individuals. In one example, a graphical display is divided into regions representing different emotions. Input indicative of an emotion is received from individuals located in an area of interest. As the input is received, a set of indicators is output in each of the regions of the graphical display. Each indicator represents a different one of the individuals who is experiencing the emotion associated with the region in which the indicator is displayed and is displayed with a color assigned to the emotion. The indicators are animated to move over time toward a center of the graphical display and are removed upon reaching the center of the graphical display. In this way, the graphical display depicts a current mood for the group and indicates a rate of change of each of the different emotions.

Abstract: A method of visualizing a plurality of designs which comply with a plurality of objectives. The method comprises acquiring a plurality of designs each represented by sequential multivariate data indicative of a compliance with a plurality of objectives, generating an objective anchored based self-organizing map (SOM) having a plurality of objective anchors and maps the plurality of designs in an objective space, and outputting the objective anchored based SOM. Each objective anchor is associated with one of the plurality of objectives, each the design is visualized in the objective anchored based SOM by an indicator which the distance thereof from each the objective anchors is indicative of a compliance thereof with a respective the associated objective in relation to other of the plurality of objectives.

Abstract: A computerized clustering method. The method comprises receiving a spatial point dataset comprising a plurality of spatial points in a space, heuristically calculating, using a processor, a plurality of ?-shape based segmentations such that each of the plurality of ?-shape based segmentations defines a plurality of polygonal areas that cluster the plurality of spatial points in a plurality of clusters which collectively bounds the plurality of spatial points, presenting to an operator in each sequential iteration of a plurality of sequential iterations another of the plurality of ?-shape based segmentations, and selecting by the operator one or more of the plurality of ?-shape based segmentations.

Abstract: Systems and methods for presentation of value distributions in a graphical user interface are provided. The method comprises computing a plurality of value distributions based on measurements performed for target values for one or more positions spread across a space, wherein a series of measurements are performed for at least a target point in the space; computing a cumulative distribution for the plurality of value distributions associated with the target point along predetermined time intervals; dividing the cumulative distribution into bins for one or more time periods corresponding to said predetermined time intervals; mapping attributes associated with the target point into shapes; and using a scaling function, assigning a color attribute from a color scheme to each bin.

Abstract: A computerized method for generating monitoring rules, comprising: presenting to a user a spatio-temporal data indicative of a plurality of spatio-temporal attributes of a plurality of image objects in a space during a period; selecting, by a user, at least one of a spatial pattern and a temporal pattern represented in said spatio-temporal data; analyzing said at least one of a spatial pattern and a temporal pattern to identify at least one of a spatial related characteristic of at least some of said plurality of image objects and a temporal related characteristic of at least some of said plurality of image objects; automatically generating at least one monitoring rule to track an occurrence of said at least one of a location related characteristic and a temporal related characteristic.

Abstract: An apparatus for visualizing data includes memory for storing sensor data and a processor. The processor is configured to generate a map of a geographic area, and to display at a first location on the map at least one icon graphically representing a measurement of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: A method for visualizing data includes generating on a display device a map including a first location and generating on the display device at least one icon graphically representing measurements of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: A computerized visualization method for illustrating multi-dimensional data, comprising: receiving a plurality of location data points, each location data point having a plurality of measured features; choosing at least one location dimension from received said plurality of dimensions; grouping said plurality of location data points into a plurality of location groups according to chosen said at least one location dimension; plotting, by a processor, said plurality of location groups as a plurality of flower charts, each said plurality of flower charts, having a plurality of pie sectors, illustrates remaining said plurality of measured features subsequent to said choosing at least one location dimension; and positioning each said plurality of flower charts, in a visual representation, according to chosen said plurality of location dimensions.

Abstract: Techniques are described for visualizing the mood of a group of individuals. In one example, a graphical display is divided into regions representing different emotions. Input indicative of an emotion is received from individuals located in an area of interest. As the input is received, a set of indicators is output in each of the regions of the graphical display. Each indicator represents a different one of the individuals who is experiencing the emotion associated with the region in which the indicator is displayed and is displayed with a color assigned to the emotion. The indicators are animated to move over time toward a center of the graphical display and are removed upon reaching the center of the graphical display. In this way, the graphical display depicts a current mood for the group and indicates a rate of change of each of the different emotions.

Abstract: A method for visualizing data includes generating on a display device a map including a first location and generating on the display device at least one icon graphically representing measurements of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: An apparatus for visualizing data includes memory for storing sensor data and a processor. The processor is configured to generate a map of a geographic area, and to display at a first location on the map at least one icon graphically representing a measurement of the sensor at the first location over a period of time and graphically representing the period of time.

Abstract: Methods, system and computer program products for spatiotemporal encounters detection of a plurality of moving objects are disclosed. The method includes receiving a dataset of a plurality of objects moving in a domain, structuring the dataset in a data structure to detect a plurality of spatiotemporal encounters among the plurality of objects, outputting a list of the detected spatiotemporal encounters. The plurality of spatiotemporal encounters may be detected in a single sweep over the received dataset.

Abstract: A method of visualizing a plurality of designs which comply with a plurality of objectives. The method comprises acquiring a plurality of designs each represented by sequential multivariate data indicative of a compliance with a plurality of objectives, generating an objective anchored based self-organizing map (SOM) having a plurality of objective anchors and maps the plurality of designs in an objective space, and outputting the objective anchored based SOM. Each objective anchor is associated with one of the plurality of objectives, each the design is visualized in the objective anchored based SOM by an indicator which the distance thereof from each the objective anchors is indicative of a compliance thereof with a respective the associated objective in relation to other of the plurality of objectives.

Abstract: Systems and methods for presentation of value distributions in a graphical user interface are provided. The method comprises computing a plurality of value distributions based on measurements performed for target values for one or more positions spread across a space, wherein a series of measurements are performed for at least a target point in the space; computing a cumulative distribution for the plurality of value distributions associated with the target point along predetermined time intervals; dividing the cumulative distribution into bins for one or more time periods corresponding to said predetermined time intervals; mapping attributes associated with the target point into shapes; and using a scaling function, assigning a color attribute from a color scheme to each bin.