Abstract:
A clustering method for a point of interest and a related apparatus are provided. The clustering method for a point of interest includes: acquiring a locating point set of a user within a preset period; generating a stay point set according to the locating point set, where each stay point in the stay point set represents one hot area; calculating a confidence level of each stay point in the stay point set; obtaining a trusted stay point from the stay point set by means of screening according to the confidence level of each stay point in the stay point set; and clustering density-connected trusted stay points to form a point of interest. By using technical solutions provided in the present disclosure, reliability and reference value of a POI can be effectively improved.
Abstract:
A touch interaction processing method, device, and system. The touch interaction processing method includes: receiving first information sent by an electromyographic signal collection device and second information sent by a location capturing device (101); if it is determined that a time gap between a first touch start time and a second touch start time is less than a preset threshold, and a quantity of touch points that is corresponding to a hand gesture is the same as a quantity of touch points that is included in the second information, generating a touch instruction, where the touch instruction includes a device identifier of the electromyographic signal collection device, the hand gesture, and coordinate information of each touch point (103); and performing an interaction operation corresponding to the touch instruction (105).
Abstract:
A target monitoring method, a camera, a controller, and a target monitoring system, where the system includes a first camera and a second camera. An overlapping area exists between fields of view of the first camera and the second camera. The method includes obtaining, location information of a to-be-tracked target in a first monitoring picture when the first camera is used as a current primary monitoring camera, determining, based on the location information of the target in the first monitoring picture, whether a location of the target in the first monitoring picture is in the overlapping area, where the overlapping area is an overlapping range between the fields of view of the first camera and the second camera, and switching, the current primary monitoring camera to the second camera when the location of the target in the first monitoring picture is in the overlapping area.
Abstract:
The present invention relates to the field of natural human-computer interaction technologies, and discloses a bioelectricity-based control method and apparatus, and a bioelectricity-based controller, so as to improve naturalness of human-computer interaction. The method is as follows: performing characteristic extraction on a collected surface electromyography signal generated when a user performs a finger press operation, so as to obtain characteristic information; determining, according to a pre-created finger type recognition template, a finger type that is used to perform the finger press operation and that is corresponding to the obtained characteristic information; and mapping the determined finger type used to perform the finger press operation to a corresponding first instruction, and controlling a controlled device according to the first instruction. In this way, the controlled device may be controlled in a more harmonious and natural human-computer interaction manner.
Abstract:
A method for predicting a position of a mobile user, and equipment are provided. The method includes determining an occurrence probability of a current behavioral activity of the mobile user; determining an occurrence probability of a target behavioral activity of the mobile user according to the occurrence probability of the current behavioral activity of the mobile user, a historical activity migration rule of the mobile user, and a public activity migration rule; determining the target behavioral activity of the mobile user according to the occurrence probability of the target behavioral activity of the mobile user; and predicting a target geographical position of the mobile user according to the determined target behavioral activity of the mobile user. The method improves usability of the target geographical position of the mobile user.
Abstract:
An action recognition method based on a surface electromyography signal includes obtaining surface electromyography signals of multiple channels, determining a valid surface electromyography signal according to the surface electromyography signals of the multiple channels, determining a frequency of the valid surface electromyography signal, and determining, according to the frequency of the valid surface electromyography signal, a body action corresponding to the surface electromyography signals of the multiple channels. A frequency of a surface electromyography signal is irrelevant to a feature such as signal strength, therefore, the method can significantly improve accuracy of action recognition based on a surface electromyography signal. Moreover, with a frequency being used as a recognition feature, a user does not need to conduct an action with a large range, which brings better user experience.
Abstract:
A clustering method for a point of interest and a related apparatus are provided. The clustering method for a point of interest includes: acquiring a locating point set of a user within a preset period; generating a stay point set according to the locating point set, where each stay point in the stay point set represents one hot area; calculating a confidence level of each stay point in the stay point set; obtaining a trusted stay point from the stay point set by means of screening according to the confidence level of each stay point in the stay point set; and clustering density-connected trusted stay points to form a point of interest. By using technical solutions provided in the present disclosure, reliability and reference value of a POI can be effectively improved.
Abstract:
A pedestrian navigation processing method and system, and a terminal device. The pedestrian navigation processing method includes determining, according to a current position of a user and navigation planning route information, a road section on which the user is currently located, wherein the navigation planning route information includes route information of all road sections between a departure place and a destination, obtaining a road width of the road section according to a positioning result obtained when the user walks on the road section and route information of the road section, determining, according to the road width, a navigation prompt time corresponding to the road section, and performing navigation prompting for the user according to the navigation prompt time. The technical solutions may perform accurate navigation for a pedestrian.
Abstract:
A terminal device includes a central processing unit, a data memory, a first selector, and a digital-to-analog conversion module. The data memory includes a first data storage apparatus and a second data storage apparatus. A first output end of the central processing unit is connected to an input end of the first selector. A second output end of the central processing unit is connected to a gating end of the first selector. An output end of the second data storage apparatus is connected to an input end of the digital-to-analog conversion module. The digital-to-analog conversion module is configured to send repeatedly a periodic signal to a receiving device within a sending time.
Abstract:
A data protection circuit of a chip, a chip, and an electronic device, where the data protection circuit performs bit width expansion and scrambling processing on a first alarm signal using an operation circuit to obtain a second alarm signal, and outputs the second alarm signal to a processing circuit. The processing circuit performs descrambling processing after receiving the second alarm signal to obtain a descrambling result. When the second alarm signal is attacked, the descrambling fails, and the descrambling result is an active level. The processing circuit outputs the descrambling result to a reset request circuit, and the reset request circuit generates a reset request signal according to the descrambling result.