Abstract: This invention discloses digitally printed plate, the manufacturing method and applications thereof, is characterized in that the digitally printed plate is of respectively from top to bottom surface lacquer layer, texture layer, second wear layer, first wear layer, pattern layer, bottom lacquer layer, base layer. The digitally printed plated has various patterns, with sufficient materials, printing unrepeatable stereoscopic pattern is possible, so it can satisfy customers' personalized customization requirements, without wasting abundant time or cost, and with process reduced, production efficiency is improved, enabling order manufacturing order insert and sample making at any time.

Abstract: Methods, apparatus and systems for determining a region attribute, and electronic devices are provided. In one aspect, a method includes: identifying a marker line in a target map, the target map being a map of a to-be-cleaned target scene, an intelligent cleaning device relying on the target map during a cleaning process, determining an enclosed region and an unenclosed region with a first position as a reference point in the target map, based on the identified marker line and an auxiliary object in the target map, the auxiliary object including a map boundary and an obstacle, the first position being a position of a preset reference object in the target map, determining the enclosed region as a user-defined cleaning region for the cleaning process of the intelligent cleaning device, and determining the unenclosed region as a normal cleaning region for the cleaning process of the intelligent cleaning device.

Abstract: Methods, devices, and systems for identifying charging devices are provided. In one aspect, a method of identifying a charging device include: capturing an infrared image and a depth image of a current field of view with a depth camera; determining, according to the infrared image, that there are one or more suspected charging device areas that satisfy first specified conditions; determining, according to the depth image, that there is a target charging device area whose height relative to a depth camera is within a specified range in the one or more suspected charging device areas; and identifying the charging device according to the target charging device area. The first specified conditions indicate that a gray-scale value of each of pixels in an area is greater than a second specified value, and a number of the pixels in the area is greater than a third specified value.

Abstract: A cleaning method and a cleaning robot are provided. The method includes: after the cleaning robot obtains a cleaning instruction for a target scene, acquiring a current power of the cleaning robot and a scene map for the target scene; if it is determined that the current power is insufficient to clean all areas to be cleaned in the target scene, determining a target cleaning area from all the areas to be cleaned in the target scene, based on a target dirtiness level for each of the areas to be cleaned; cleaning the target cleaning area based on the scene map, the target dirtiness level for the target cleaning area and the current power. A more intelligent cleaning robot and a more reasonable cleaning process are realized.

Abstract: The embodiments of the present application provides a target detection method, which comprises: obtaining a plurality of images acquired by an image acquiring device as images to be detected when a region to be detected is illuminated by light sources with different illuminating angles, wherein the different illuminating angles correspond to the different images to be detected (S101); and determining whether a target exists in the region to be detected based on gray scale differences between the obtained images to be detected with illuminating by the light sources of with different illuminating angles (S102). The method is applied to achieve a simple and effective detection of the target existing in the region to be detected.

Abstract: Methods, devices, and systems for identifying charging devices are provided. In one aspect, a method of identifying a charging device include: capturing an infrared image and a depth image of a current field of view with a depth camera; determining, according to the infrared image, that there are one or more suspected charging device areas that satisfy first specified conditions; determining, according to the depth image, that there is a target charging device area whose height relative to a depth camera is within a specified range in the one or more suspected charging device areas; and identifying the charging device according to the target charging device area. The first specified conditions indicate that a gray-scale value of each of pixels in an area is greater than a second specified value, and a number of the pixels in the area is greater than a third specified value.

Abstract: Methods, apparatus and systems for determining a region attribute, and electronic devices are provided. In one aspect, a method includes: identifying a marker line in a target map, the target map being a map of a to-be-cleaned target scene, an intelligent cleaning device relying on the target map during a cleaning process, determining an enclosed region and an unenclosed region with a first position as a reference point in the target map, based on the identified marker line and an auxiliary object in the target map, the auxiliary object including a map boundary and an obstacle, the first position being a position of a preset reference object in the target map, determining the enclosed region as a user-defined cleaning region for the cleaning process of the intelligent cleaning device, and determining the unenclosed region as a normal cleaning region for the cleaning process of the intelligent cleaning device.

Abstract: A cleaning method and a cleaning robot are provided. The method includes: after the cleaning robot obtains a cleaning instruction for a target scene, acquiring a current power of the cleaning robot and a scene map for the target scene; if it is determined that the current power is insufficient to clean all areas to be cleaned in the target scene, determining a target cleaning area from all the areas to be cleaned in the target scene, based on a target dirtiness level for each of the areas to be cleaned; cleaning the target cleaning area based on the scene map, the target dirtiness level for the target cleaning area and the current power. A more intelligent cleaning robot and a more reasonable cleaning process are realized.

Abstract: The embodiments of the present application provides a target detection method, which comprises: obtaining a plurality of images acquired by an image acquiring device as images to be detected when a region to be detected is illuminated by light sources with different illuminating angles, wherein the different illuminating angles correspond to the different images to be detected (S101); and determining whether a target exists in the region to be detected based on gray scale differences between the obtained images to be detected with illuminating by the light sources of with different illuminating angles (S102). The method is applied to achieve a simple and effective detection of the target existing in the region to be detected.

Abstract: A data object can be represented based on multiple “tags” (e.g., multiple signatures provided as a cluster of signatures based on multiple tags of a data model). Essentially, the representation of the data object need not necessarily reflect the entire data object but it can provide a useful indication (or a signal) (e.g., “s40={computer vision, image analysis, tracking, detection, 3d}”), In addition, a data representation provided (e.g., signature or cluster of signatures) can represent multiple data objects. However, a data object can be represented by multiple tags (e.g., signatures) as well. Also, multiple tags can be used to collectively represent a data object. The tags can provide information in an organized and logically structured manner. For example, a cluster signature can be provided with strings of one or more words (e.g., keywords) concatenated with logical operators (e.g., AND, OR, NOT).

Abstract: A data object can be represented based on multiple “tags” (e.g., multiple signatures provided as a cluster of signatures based on multiple tags of a data model). Essentially, the representation of the data object need not necessarily reflect the entire data object but it can provide a useful indication (or a signal) (e.g., “s40={computer vision, image analysis, tracking, detection, 3d}”), In addition, a data representation provided (e.g., signature or cluster of signatures) can represent multiple data objects. However, a data object can be represented by multiple tags (e.g., signatures) as well. Also, multiple tags can be used to collectively represent a data object. The tags can provide information in an organized and logically structured manner. For example, a cluster signature can be provided with strings of one or more words (e.g., keywords) concatenated with logical operators (e.g., AND, OR, NOT).

Abstract: An apparatus and method for generating an application container are provided. The method includes selecting a target application from among a plurality of applications included in an electronic device, acquiring a policy file corresponding to the target application, determining whether the policy file includes a category of the target application, and executing the application container which includes the target application.

Abstract: A system and method are presented for providing generic single sign-on in an electronic device. Information is received that identifies one or more applications and associated identity authenticators and a whitelist of the identified applications and authenticators is created. A request for an access token is received from a requesting application. If the requesting application is listed in the whitelist, an authenticator associated with the requesting application is determined and a request for an access token is sent to the associated authenticator. In response to the request, an access token is received from the authenticator and the access token is sent to the requesting application. If the requesting application is not listed in the whitelist, a predefined response message is sent to the requesting application.

Abstract: The present disclosure provides an image acquisition method and apparatus and a video monitoring method and system. The image acquisition method is applied in an image acquisition apparatus in a video monitoring system, wherein the image acquisition apparatus is provided with a WiFi detector and an image capturing component; the method comprises: using the image capturing component to acquire a human image containing a human body feature in a target environment; using the WiFi detector to detect and obtain unique identification information of at least one WiFi terminal located in the target environment; enabling the human image and the unique identification information of the at least one WiFi terminal to correspond to each other to generate image data of the human image containing the human body feature and the unique identification information.

Abstract: A first distance between a first node and a target node is computed based on a first time-of-flight (ToF) of a communication sequence between the first node and the target node. A second distance between a second node and the target node is computed based on a second ToF of the communication sequence between the first node and the target node, as recorded by the second node. A location of the target node is determined based on the first distance and the second distance.

Abstract: An apparatus and method to authorize Application Programming Interface (API) or method level access in system and application services are provided. The method includes receiving a request for access to a service from another service or an application via an interface accessible by the other service or the application, and determining whether to authorize the request based at least in part on a specified policy.

Abstract: Provided are a video monitoring method and system based on smart home. In the method and the system, a triggering condition of image capturing is preset and stored, wherein the triggering condition is appearance of a specific person in an image and specific performance of the specific person; whether a current image meets the triggering condition or not is detected in real time; when a detecting result is that the current image meets the triggering condition, the current image is captured, the captured image is classified according to different specific performance of the specific person, and the classified image is stored in a timeline form; and an access right and a sending right are set for the classified image stored in the timeline form.