Provided are a detection method for a sound source and a detection device therefor, which are capable of accurately detecting the position of a sound source through use of measurement results of sound intensities. In the detection method, I.sub.all=(I.sub.x.sup.2+I.sub.y.sup.2+I.sub.z.sup.2), which is a total value of the sound intensities I.sub.x, I.sub.y, and I.sub.z in three axial directions (x-, y-, and z-axis directions) orthogonal to each other at a sound receiving point (P) in a sound field, is calculated, and then the position of the sound source is estimated after extracting the sound source by performing processing with averaged values within a predetermined peak width instead of the magnitude of a peak in a sound intensity waveform of the total value, or the position of the sound source is estimated after extracting the sound source with attention being given to a spatial travel speed of a sound intensity or a sound particle velocity of the total value.

A positioning system and method thereof are provided in this disclosure. The positioning method includes steps of: emitting a radiation from a first electronic apparatus to a second electronic apparatus and starting to accumulate a time count; sensing the radiation on the second electronic apparatus and sending a first ultrasonic signal from the second electronic apparatus to the first electronic apparatus; sensing the first ultrasonic signal by a plurality of ultrasound sensors on the first electronic apparatus and calculating a plurality of first time periods started from the radiation is emitted until the first ultrasonic signal is sensed by the ultrasound sensors; calculating a plurality of first relative distances between the ultrasound sensors and a first ultrasound emitter on the second electronic apparatus; and locating a first relative position of the second electronic apparatus relative to the first electronic apparatus according to the first relative distances.

A positioning system and method thereof are provided in this disclosure. The positioning method includes steps of: emitting a radiation from a first electronic apparatus to a second electronic apparatus and starting to accumulate a time count; sensing the radiation on the second electronic apparatus and sending a first ultrasonic signal from the second electronic apparatus to the first electronic apparatus; sensing the first ultrasonic signal by a plurality of ultrasound sensors on the first electronic apparatus and calculating a plurality of first time periods started from the radiation is emitted until the first ultrasonic signal is sensed by the ultrasound sensors; calculating a plurality of first relative distances between the ultrasound sensors and a first ultrasound emitter on the second electronic apparatus; and locating a first relative position of the second electronic apparatus relative to the first electronic apparatus according to the first relative distances.

An entity-tracking computing system receives sensor information from a plurality of different sensors. The positions of entities detected by the various sensors are resolved to an environment-relative coordinate system so that entities identified by one sensor can be tracked across the fields of detection of other sensors.

An entity-tracking computing system receives sensor information from a plurality of different sensors. The positions of entities detected by the various sensors are resolved to an environment-relative coordinate system so that entities identified by one sensor can be tracked across the fields of detection of other sensors.

Examples are disclosed herein that relate to entity tracking. One examples provides a computing device comprising a logic processor and a storage device holding instructions executable by the logic processor to receive image data of an environment including a person, process the image data using a face detection algorithm to produce a first face detection output at a first frequency, determine an identity of the person based on the first face detection output, and process the image data using another algorithm that uses less computational resources of the computing device than the face detection algorithm. The instructions are further executable to track the person within the environment based on the tracking output, and perform one or more of updating the other algorithm using a second face detection output, and updating the face detection algorithm using the tracking output.

Examples are disclosed herein that relate to entity tracking. One examples provides a computing device comprising a logic processor and a storage device holding instructions executable by the logic processor to receive image data of an environment including a person, process the image data using a face detection algorithm to produce a first face detection output at a first frequency, determine an identity of the person based on the first face detection output, and process the image data using another algorithm that uses less computational resources of the computing device than the face detection algorithm. The instructions are further executable to track the person within the environment based on the tracking output, and perform one or more of updating the other algorithm using a second face detection output, and updating the face detection algorithm using the tracking output.

A method for use with a computing device is provided. The method may include executing one or more programs of an intelligent digital assistant system at a processor and presenting a user interface to a user. At the processor, the method may include receiving natural language user input from the user, parsing the user input at an intent handler to determine an intent template with slots, populating the slots in the intent template with information from user input, and performing resolution on the intent template to partially resolve unresolved information. If a slot with missing slot information exists in the partially resolved intent template, a loop may be executed at the processor to fill the slots. The method may include, at the processor, determining that all required information is available and resolved and generating a rule based upon the intent template with all required information being available and resolved.

A method for use with a computing device is provided. The method may include executing one or more programs of an intelligent digital assistant system at a processor and presenting a user interface to a user. At the processor, the method may include receiving natural language user input from the user, parsing the user input at an intent handler to determine an intent template with slots, populating the slots in the intent template with information from user input, and performing resolution on the intent template to partially resolve unresolved information. If a slot with missing slot information exists in the partially resolved intent template, a loop may be executed at the processor to fill the slots. The method may include, at the processor, determining that all required information is available and resolved and generating a rule based upon the intent template with all required information being available and resolved.

Example implementations relate to determining a location using time difference of arrival (TDOA). For example, a computing device may include a first sensor to receive a signal at a first time, where the signal is generated by a user contact at a particular location on a keyboard associated with the computing device. The computing device also includes a second sensor to receive the signal at a second time and a third sensor to receive the signal at a third time. The computing device may also include a processor. The processor may calculate a set of TDOAs associated with the first time, the second time, and the third time. The processor may determine the particular location of the user contact using a triangulation based on the set of TDOAs and may identify a character on the keyboard, where the character is associated with the particular location.