Abstract: An example system is provided in according with one implementation of the present disclosure, The system includes a 3D display displaying at least one three-dimensional (3D) visualization, an auxiliary computing device including a multi-touch display and a plurality of sensors, and a behavior analysis engine to perform a behavior analysis of a user by using data from the plurality of sensors. The behavior analysis engine is to: determine an attention engagement level of the user, and determine a pose of the user in relation to the auxiliary computing device. The system further includes an intention analysis engine to determine an intention of the user in relation to the at least one 3D visualization based on the users attention engagement level and the users pose, and an interaction mode engine to automatically adjust the system to an interaction mode based on the identified user intention.

Abstract: Examples disclosed herein relate to viewing device adjustment based on eye accommodation in relation to a display. In one implementation, a computing device determines accommodation information related to a viewer's focus on an image rendered on a display. The computing device may cause an optical component associated with a viewing device to adjust based on the determined accommodation.

Abstract: In one example of the disclosure, presence data indicative of a presence factor for a remote subject is received from a server. The presence data is analyzed and a display representative of the presence factor is caused at a 3D object. The 3D object includes a 3D element representative of the remote subject.

Abstract: In an example, high-dimensional data is projected to a multi-dimensional space to differentiate clusters of the high-dimensional data. A user selection of at least two of the clusters may be received and a plurality of dissimilar dimensions may be extracted from the at least two clusters. In addition, a user selected of a dissimilar dimension from the plurality of extracted dissimilar dimensions may be received. In response to receipt of the user selection of the dissimilar dimension from the plurality of dissimilar dimensions, a plurality of correlated dimensions to the dissimilar dimension may be determined. In addition, the plurality of dissimilar dimensions and the plurality of correlated dimensions may be displayed.

Abstract: A user-selected group of data points is received. Weighted distances between further data points with the user-selected group of data points are computed, the weighted distances computed based on respective weights assigned to dimensions of data points. Density-based grouping of the further data points is performed based on the computed weighted distances, the density-based grouping producing cohorts of data points. A graphical visualization is generated including pixels representing the user-selected group of data points and the cohorts of data points. The graphical visualization provides a temporal-based visualized identification of the cohorts with the user selected group of data points.

Abstract: Visualization of a cohort for high-dimensional categorical data is disclosed. One example is a system including a display module to identify real-time selection of a query data element in an interactive visual representation of high-dimensional categorical data elements comprising a plurality of categorical components. A matrix generator generates a binary distance matrix with columns representing categorical components, and entries in a row indicative of a degree of similarity of respective categorical components of the selected query data element to a data element represented by the row, and determines a category weighting matrix by associating a weight with entries in each column of the binary distance matrix. An evaluator evaluates a weighted similarity score for a data element represented by a row of the category weighting matrix based on entries of the row. A selector iteratively and interactively selects, based on weighted similarity scores, a cohort of categorical data elements.

Abstract: Visually interactive and iterative analysis of data patterns by a user is disclosed. One example is a system including a display module and an interaction processor. The display module displays, via an interactive graphical user interface, a visual representation of a plurality of data elements and respective data relations between the data elements, and wherein each data element is represented by pixel attributes of a pixel. The interaction processor iteratively and interactively processes analysis by a user based on identifying selection, by the user, of an arbitrarily shaped region of the visual representation, clipping the selected region by zooming in to the selected region, identifying, in the clipped region, selection of data elements of interest to the user, and prompting the display module to automatically blur visual representations of data elements different from the data elements of interest by modifying the pixel attributes of respective pixels.

Abstract: A unified visualization interface is disclosed. One example is a system including an association module, a multicasting module, a data sharing module, and a unified visualization interface. The association module associates an identified event in a first visualization system with a visualization function. The multicasting module stores event data related to the identified event and the associated visualization function in a shared data source, and multicasts the identified event to a second visualization system. The data sharing module associates the event data with characteristics of the first visualization system, and shares, in response to the multicast of the identified event, the shared data source with the second visualization system.

Abstract: Similarities between events that include a plurality of dimensions are computed, the similarities computed based on binary comparisons between the events and based on user-specified weights for the dimensions. Multidimensional scaling (MDS) values are calculated based on the computed similarities between the events. A graphical visualization is generated of a temporal plot of the events, the temporal plot comprising a first axis corresponding to time, and a second axis corresponding to the MDS values, and the temporal plot representing overlapping time slices each containing pixels representing a respective subset of the events.

Abstract: Visually interactive identification of a cohort of similar data objects is disclosed. One example is a system including a data processor to access a plurality of data objects, each data object comprising a plurality of numerical components, where each component represents a data feature of a plurality of data features, and to identify, for each data feature, a feature distribution of the numerical components. A selector selects a sub-plurality of the data features of a query object, where a given data feature is selected if the component representing the given data feature is a peak for the feature distribution. An evaluator determines a similarity measure based on the sub-plurality of the data features. An interaction processor iteratively processes selection of a sub-plurality of the data features based on domain knowledge, and identifies, based on the similarity measures, a cohort of data objects similar to the query object.

Abstract: An example method is provided in according with one implementation of the present disclosure. The method includes identifying an intention of a user of a system in relation to a three-dimensional (3D) virtual object and selecting a 3D navigation mode from a plurality of 3D navigation modes based on the identified user intention. The plurality of 3D navigation modes includes at least a model navigation mode, a simple navigation mode, a driving navigation mode, a reaching navigation mode, and a multi-touch navigation mode. The method further includes transitioning the system to the selected 3D navigation mode.

Abstract: A system for providing a two-way interactive 3D experience includes a first video capture system configured to capture a first set of images of a first person in a first location, and a first display system in the first location. A second video capture system is configured to capture a second set of images of a second person in a second location. A second display system is in the second location. A two-way communication link is configured to deliver the first set of images to the second display system for display and deliver the second set of images to the first display system for display. The second display system is configured to generate a substantially life-sized 3D display of the first person based on the first set of images.

Abstract: A visualization includes a multidimensional array of multidimensional graphlets, the multidimensional array arranging the multidimensional graphlets in a plurality of dimensions, where each of the multidimensional graphlets includes at least three dimensions. Respective attributes of data are represented with the plurality of dimensions of the multidimensional array. Respective additional attributes of the data are represented with the dimensions of the multidimensional graphlets.

Abstract: A system for providing a two-way interactive 3D experience includes a first video capture system configured to capture a first set of images of a first person in a first location, and a first display system in the first location. A second video capture system is configured to capture a second set of images of a second person in a second location. A second display system is in the second location. A two-way communication link is configured to deliver the first set of images to the second display system for display and deliver the second set of images to the first display system for display. The second display system is configured to generate a substantially life-sized 3D display of the first person based on the first set of images.

Abstract: In an example, high-dimensional data is projected to a multi-dimensional space to differentiate clusters of the high-dimensional data. A user selection of at least two of the clusters may be received and a plurality of dissimilar dimensions may be extracted from the at least two clusters. In addition, a user selected of a dissimilar dimension from the plurality of extracted dissimilar dimensions may be received. In response to receipt of the user selection of the dissimilar dimension from the plurality of dissimilar dimensions, a plurality of correlated dimensions to the dissimilar dimension may be determined. In addition, the plurality of dissimilar dimensions and the plurality of correlated dimensions may be displayed.

Abstract: Selected topics are identified from records based on scoring candidate terms in the records according to a user-specified metric and at least one further metric selected from among frequencies of occurrence of records pertaining to the respective candidate terms, and negativity of sentiment expressed with respect to the candidate terms in the records. A visualization is generated that includes bubbles representing the respective topics, the bubbles including pixels representing corresponding records, where a given one of the bubbles has a shape dependent upon a number of records represented by the given bubble and a time interval represented by the given bubble. Visual indicators are assigned to the pixels in the given bubble according to values of an attribute expressed in the corresponding records for the topic represented by the given bubble.

Abstract: A system for providing a two-way interactive 3D experience includes a first video capture system configured to capture a first set of images of a first person in a first location, and a first display system in the first location. A second video capture system is configured to capture a second set of images of a second person in a second location. A second display system is in the second location. A two-way communication link is configured to deliver the first set of images to the second display system for display and deliver the second set of images to the first display system for display. The second display system is configured to generate a substantially life-sized 3D display of the first person based on the first set of images.

Abstract: According to an example, fluctuations of a metric for events are determined. The fluctuations are for multiple time intervals. A pixel-based visualization of the fluctuations is generated, and the pixels represent amounts of the fluctuations.

Abstract: A technique for force feedback can include displaying a data set in a visual model. A technique for force feedback can include selecting a portion of the data instances in the data set. A technique for force feedback can also include providing a force feedback via a force feedback device as an interaction point interacts with the portion of the data instances.

Abstract: A display system includes a plurality of individual display devices to collectively generate an image on a display surface. At least one camera captures at least one image of the image on the display surface and captures at least one image of an object positioned near the display surface. A controller automatically adjusts a color of an object appearing in the image on the display surface based on the at least one image of an object.