Abstract: A neutral facial expression of a wearer of a head-mountable display (HMD) is detected based on signals received from one or multiple facial electromyographic (fEMG) sensors of the HMD. A baseline neutral facial expression image of the wearer is responsively automatedly captured using one or multiple cameras of the HMD. HMD camera-based detection of facial expressions of the wearer is calibrated based on the automatedly captured baseline neutral facial expression image.

Abstract: Examples are described herein for determining aggregate psychological states of multiple individuals. In various examples, sensor data indicative of affects of multiple individuals may be analyzed. Based on the analyzing, the multiple individuals may be partitioned into multiple distinct clusters of individuals. An aggregate psychological state of the individuals of a given cluster of the multiple distinct clusters of individuals may be determined. Data indicative of the aggregate psychological state may be transmitted to cause a computing device to render output that conveys the aggregate psychological state of the individuals of the cluster.

Abstract: Methods, systems, apparatus, and computer-readable media (transitory or non-transitory) are described herein for inferring psychological states. In various examples, data indicative of a measured affect of an individual may be processed using a regression model to determine a coordinate in a continuous space. The continuous space may be indexed based on a plurality of discrete psychological labels. In a first context, the coordinate in the continuous space may be mapped to one of a first set of the discrete psychological labels associated with the first context. In a second context, the coordinate in the continuous space may be mapped to one of a second set of the discrete psychological labels associated with the second context.

Abstract: An example system includes a plurality of biometric sensors. The system also includes a first classifier engine to produce a first latent space representation of a first signal from a first biometric sensor of the plurality of biometric sensors. The system includes a second classifier engine to produce a second latent space representation of a second signal from a second biometric sensor of the plurality of biometric sensors. The system includes an attention engine to weight the first latent space representation and the second latent space representation based on correlation among latent space representations. The system includes a final classifier engine to determine a characteristic of a user based on the weighted first and second latent space representations.

Abstract: An example system includes a plurality of biometric sensors to generate a plurality of signals. The system includes a feature engine to generate a plurality of feature vectors from the plurality of signals. The system includes a classifier engine to generate a plurality of decision vectors based on the plurality of feature vectors. The system includes an attention engine to weight the plurality of feature vectors and the plurality of decision vectors and determine a characteristic of a user based on the weighted feature and decision vectors.

Abstract: Systems and methods of visual mining of user behavior patterns are disclosed. A plurality of clickstreams may be received. Each clickstream may represent a corresponding sequence of user actions. A visual representation of each clickstream may be caused to be displayed on a device. Each visual representation may comprise a distinct graphical element for each user action of the corresponding clickstream, and each visual representation may be configured to indicate a frequency level of the corresponding clickstream. Each distinct graphical element may comprise a geometric shape and a corresponding color that distinctly represents the corresponding user action. Graphical elements of each visual representation may comprise a size that is proportional to the frequency level of the corresponding clickstream. An indication of a selection of one of the visual representations may be received, and additional information about the corresponding clickstream may be caused to be displayed on the device.

Abstract: Examples for geometry-aware interactive design are described herein. In some examples, a computing device may extract geometric information from an input image of an object. The computing device may generate an output image by a generator network based on the extracted geometric information, a latent space vector of the input image and a sketch input.

Abstract: A method of removing individual variation from emotional representations may include classifying physiological data based on subject-independent emotion factors. The subject-independent emotion factors are isolated from subject-dependent individual factors. Further, a non-transitory computer readable medium includes computer usable program code embodied therewith. The computer usable program code, when executed by the processor classifies, with a first neural network, the physiological data based on subject-independent emotion factors from the trained first neural network. The subject-independent emotion factors have been isolated within the physiological data from subject-dependent individual factors.

Abstract: An example system includes a sketch interface to receive a sketch input from a user, an object model reservoir to store models of objects, a generator to generate additional models of objects, and a sample matching portion. The additional models generated by the generator are to be added to the object model reservoir. The sample matching portion is to select at least one matched object model from the reservoir to match to the sketch input from the user. The generator is to generate the additional models based on the matched object model.

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: Systems and methods of visual mining of user behavior patterns are disclosed. A plurality of clickstreams may be received. Each clickstream may represent a corresponding sequence of user actions. A visual representation of each clickstream may be caused to be displayed on a device. Each visual representation may comprise a distinct graphical element for each user action of the corresponding clickstream, and each visual representation may be configured to indicate a frequency level of the corresponding clickstream. Each distinct graphical element may comprise a geometric shape and a corresponding color that distinctly represents the corresponding user action. Graphical elements of each visual representation may comprise a size that is proportional to the frequency level of the corresponding clickstream. An indication of a selection of one of the visual representations may be received, and additional information about the corresponding clickstream may be caused to be displayed on the device.

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: 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: Systems and methods of visual mining of user behavior patterns are disclosed. A plurality of clickstreams may be received. Each clickstream may represent a corresponding sequence of user actions. A visual representation of each clickstream may be caused to be displayed on a device. Each visual representation may comprise a distinct graphical element for each user action of the corresponding clickstream, and each visual representation may be configured to indicate a frequency level of the corresponding clickstream. Each distinct graphical element may comprise a geometric shape and a corresponding color that distinctly represents the corresponding user action. Graphical elements of each visual representation may comprise a size that is proportional to the frequency level of the corresponding clickstream. An indication of a selection of one of the visual representations may be received, and additional information about the corresponding clickstream may be caused to be displayed on the device.

Abstract: Interactive analysis of data based on progressive visualizations is disclosed. One example is a system including a data module, a visualization module, an interaction module, and an analytics module. The data module processes a plurality of data elements. The visualization module progressively displays, via an interactive graphical user interface, an overview visualization of a sub-plurality of the plurality of data elements, the overview visualization based on at least one of data resolution and display resolution, and a detailed visualization based on an interaction with the overview visualization. The interaction module processes the interaction with the overview visualization. The analytics module analyzes the interaction to generate a deployment rule.

Abstract: An example collaboration system is provided in according with one implementation of the present disclosure. The system includes a 3D display a 3D data visualization, at least two hand avatars of two different users, and a view field avatar. The system also includes a plurality of auxiliary computing devices and a behavior analysis engine to perform a behavior analysis of a user. 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 3D visualization based on the user's attention engagement level and the user's pose, and a collaboration engine to implement an action with the 3D data visualization by using a hand avatar based on the user's intention and an identified gesture.

Abstract: Systems and methods of visual mining of user behavior patterns are disclosed. A plurality of clickstreams may be received. Each clickstream may represent a corresponding sequence of user actions. A visual representation of each clickstream may be caused to be displayed on a device. Each visual representation may comprise a distinct graphical element for each user action of the corresponding clickstream, and each visual representation may be configured to indicate a frequency level of the corresponding clickstream. Each distinct graphical element may comprise a geometric shape and a corresponding color that distinctly represents the corresponding user action. Graphical elements of each visual representation may comprise a size that is proportional to the frequency level of the corresponding clickstream. An indication of a selection of one of the visual representations may be received, and additional information about the corresponding clickstream may be caused to be displayed on the device.

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 user's attention engagement level and the user's pose, and an interaction mode engine to automatically adjust the system to an interaction mode based on the identified user intention.

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: 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.