A simultaneous localization and mapping system for a motor vehicle is disclosed and includes a plurality of sensors disposed within a vehicle operable to detect an object proximate the vehicle and generate a plurality of data points representing sensor returns corresponding to the detected objects surrounding the vehicle, and a controller configured to receive the data points representing the sensor returns of the detected objects surrounding the vehicle, to define an occupancy grid based on the data points and to generate vehicle operating instructions based on the defined occupancy grid, wherein the controller is configured to define at least one geometric anchor from the detected data points and localizing the vehicle based on the at least one geometric anchor.

A cross-correlation system includes control circuitry that obtains first sensor data of a first user from a radio detection and ranging system. A first portable device carried by the first user is detected based on the first sensor data of the first user. Second sensor data is obtained from the first portable device based on the detection of the first portable device of the first user. The first sensor data and the second sensor data are cross-correlated to obtain cross-correlated information of the first user. A first gesture specific to the first user is recognized based on the cross-correlated information. A first controllable device is identified from a plurality of controllable devices and a first action that is to be executed at the identified first controllable device, based on the first gesture. The identified first controllable device is controlled to execute the first action based on the first gesture.

In one embodiment, a method includes an intelligent communication device detecting that a person is visible to a camera of the device, determining a first biometric characteristic of the person discernable by the device, associating the first biometric characteristic with a user identifier unique to the person, determining, while the person is identifiable based on the first biometric characteristic, a second biometric characteristic of the person discernable by the device, and associating the second biometric characteristic with the user identifier. The method also includes the device determining that a detected person has a detected biometric characteristic, determining that the detected person is associated with the user identifier by matching the detected biometric characteristic to the first biometric characteristic or the second biometric characteristic, and applying, while the detected person is identifiable based on the detected biometric characteristic, a user-specific customization associated with the user identifier.

In one aspect, a computer-implemented method corrects a multi-sphere head model used in dipole localization for a set of magnetic field sensors (MEG sensors) by replacing ghost spheres with replacement spheres that are not ghost spheres. One type of ghost sphere completely encloses the brain volume but is so large that a center of the sphere is outside the brain volume. Another type of ghost sphere lies entirely outside the brain volume. Various approaches for correcting ghost spheres are disclosed.

A method includes detecting whether one or more myocardial infarctions (MI) has occurred using vectorcardiographic (VCG) signals with gradient boosting, the VCG signals including VCG loops, and determining an MI location using the VCG signals and gradient boosting.

Techniques for audio tagging of an object of interest are provided. An object of interest within a field of view of a first video camera may be identified at a first time. At least one audio tag representing a first sound created by the object of interest may be generated and associated with the object of interest. At a second time later than the first and at a second video camera, a second sound generated by an unidentified object that is not in the field of view of the second video camera may be detected. An audio tag representing the second tag may be generated. It may be determined that the object of interest and the unidentified object of interest are the same when the audio tag representing the first sound and the second sound are the same.

A fluorescent single molecule emitter simultaneously transmits its identity, location, and cellular context through its emission patterns. A deep neural network (DNN) performs multiplexed single-molecule analysis to enable retrieving such information with high accuracy. The DNN can extract three-dimensional molecule location, orientation, and wavefront distortion with precision approaching the theoretical limit of information content of the image which will allow multiplexed measurements through the emission patterns of a single molecule.

The present technique relates to an apparatus and a method for video-audio processing, and a program each of which enables a desired object sound to be more simply and accurately separated. A video-audio processing apparatus includes a display control portion configured to cause a video object based on a video signal to be displayed; an object selecting portion configured to select the predetermined video object from the one video object or among a plurality of the video objects; and an extraction portion configured to extract an audio signal of the video object selected by the object selecting portion as an audio object signal.

A method for determining noise associated with a received signal in a telecommunications network, the received signal being sampled beforehand in the form of a succession of data. The method includes: selecting a portion of the data in the received signal and determining a given number of possible partitions of the selected portion of the data in the received signal, the number of partitions being greater than or equal to two; partitioning all of the data in the received signal into the number of partitions; estimating mean energies of the signal in each of the partitions and identifying a partition from among the partitions having a minimum mean, the identified partition being a noise partition; and estimating a variance of the noise partition, the noise associated with the received signal being a function of the variance of the noise partition.

Provided is a method of controlling an image and sound pickup device, which is includes obtaining a plurality of audio signals and a participant image, which shows a plurality of participants, and generating location information about a sound source location by using comparison information about a comparison among the plurality of audio signals and face recognition that is performed on the participant image; and generating an estimated utterer image, which displays an estimated utterer, by using the location information.