JP-2022536756-A5 -

Dates

Publication Date

20230530

Application Date

20200612

Description

While the subject matter is described in a language specific to structural features, it should be understood that the subject matter defined in the attached claims is not necessarily limited to the specific features described. Rather, specific features are disclosed as exemplary forms that implement the claims. The invention described in the original claims of this application is listed below. [1] It is a system, A handheld controller having a touch sensor array including a plurality of capacitive pads distributed on the handle of the handheld controller, One or more processors, One or more non-temporary computer-readable media for storing computer executable instructions, wherein when the computer executable instructions are executed by the one or more processors, the one or more processors... The touch sensor array receives capacitance values detected by the plurality of capacitive pads, Based at least partially on the capacitance values, a covariance matrix is generated that shows the correlation between pairs of pads among the plurality of capacitance-type pads. Determining a plurality of feature vectors based at least partially on the covariance matrix, wherein each feature vector corresponds to a pad among the plurality of capacitive pads and describes the correlation between that pad and one or more other pads among the plurality of capacitive pads, Clustering the multiple feature vectors using a clustering algorithm, A system that causes the touch sensor array of the handheld controller to be configured according to a controller configuration, at least in part on the clustering, wherein the controller configuration is configured to assign at least a first subset of the plurality of capacitive pads to a first group corresponding to the first fingers of the hand, and assign a second subset of the plurality of capacitive pads to a second group corresponding to the second fingers of the hand. [2] The plurality of capacitive pads include a set of n pads, where n is a first integer. The generation of the covariance matrix comprises generating the covariance matrix as an n × d covariance matrix based at least partially on a subset of d reference pads among the plurality of capacitive pads, where d is a second integer less than the first integer. The system according to [1], wherein the determination of the plurality of feature vectors includes determining n d-dimensional feature vectors. [3] The plurality of sensors are distributed on the handle in rows and columns of pads, the rows are oriented substantially horizontally on the handle, and the columns are oriented substantially vertically on the handle. The system according to [2], wherein the subset of d reference pads includes a row of pads. [4] The aforementioned clustering algorithm is a k-means clustering algorithm. The clustering of the plurality of feature vectors is The k-means clustering algorithm described above is used. Multiple k clusters and Initialize with input parameters that include the estimated center values of the k clusters in the d-dimensional space, Assigning each of the aforementioned feature vectors to a cluster among the k clusters having a central estimate that is the shortest distance from the feature vector, The system according to [2], which includes updating each center estimate to obtain k updated cluster centers, wherein the cluster center estimates are updated at least in part based on the feature vectors assigned to the clusters. [5] It is a method, Receiving data generated by multiple sensors of a touch sensor array of a handheld controller, wherein the multiple sensors are distributed on the handle of the handheld controller. Based at least partially on the aforementioned data, a covariance matrix is generated that shows the correlation between pairs of sensors among the plurality of sensors, Determining a plurality of feature vectors based at least partially on the aforementioned covariance matrix, wherein each feature vector corresponds to a sensor among the plurality of sensors and describes the correlation between the sensor and one or more other sensors among the plurality of sensors, Clustering the multiple feature vectors using a clustering algorithm, A method comprising configuring the touch sensor array of the handheld controller according to a controller configuration, at least in part on the clustering, wherein the controller configuration is configured such that at least a first subset of the plurality of sensors is assigned to a first group corresponding to the first fingers of the hand, and a second subset of the plurality of sensors is assigned to a second group corresponding to the second fingers of the hand. [6] The plurality of sensors includes a set of n sensors, where n is a first integer. The generation of the covariance matrix includes generating the covariance matrix as an n × d covariance matrix based at least partially on a subset of d reference sensors among the plurality of sensors, where d i