Abstract:
The present disclosure discloses a method of determining precise positioning. A method of determining precise positioning according to an embodiment of the present disclosure includes: determining at least one piece of image positioning information of at least one image object detected from at least one image; determining at least one piece of wireless positioning information of at least one wireless object on the basis of signal strength of a wireless signal; performing mapping for the at least one piece of image positioning information and the at least one piece of wireless positioning information; and determining final positioning information on the basis of the at least one piece of image positioning information, and the at least one piece of wireless positioning information for which mapping is performed.
Abstract:
Provided are a system and method for active data collection mode control for reducing crowd-sourcing signal data collection required for fingerprint database (FPDB) maintenance. The system for active data collection mode control for reducing crowd-sourcing signal data collection required for FPDB maintenance includes a mobile device configured to support a survey mode, a localization mode, and a crowd-sourcing mode and a server configured to receive data from the mobile device, generate and update an FPDB, and control a data collection mode.
Abstract:
Provided is a segmentation and tracking system based on self-learning using video patterns in video. The present invention includes a pattern-based labeling processing unit configured to extract a pattern from a learning image and then perform labeling in each pattern unit to generate a self-learning label in the pattern unit, a self-learning-based segmentation/tracking network processing unit configured to receive two adjacent frames extracted from the learning image and estimate pattern classes in the two frames selected from the learning image, a pattern class estimation unit configured to estimate a current labeling frame through a previous labeling frame extracted from the image labeled by the pattern-based labeling processing unit and a weighted sum of the estimated pattern classes of a previous frame of the learning image, and a loss calculation unit configured to calculate a loss between a current frame and the current labeling frame by comparing the current labeling frame with the current labeling frame estimated by the pattern class estimation unit.
Abstract:
Provided is a method and apparatus for creating a virtual traffic engineering (TE) link in an upper layer of an optical transport network (OTN). To create a virtual TE link, a node may determine to create the virtual TE link in an upper layer of an OTN, and may set up a forwarding adjacency (FA)-label switched path (LSP) between nodes in an OTN layer. The FA-LSP may be set up on a control plane of the OTN layer. The node may create the virtual TE link by registering the setup FA-LSP as a TE link of the upper layer of the node.
Abstract:
Provided herein is a path computation element based on Transport Network Assigned (TNA) address and a method for path computation based on User Network Interface (UNI). The path computation element and UNI based path computation method of the present disclosure minimize overhead caused by abstract Traffic Engineering (TE) link, and minimize manual environment set up, and routing information exchange and advertisements in a local domain or between domains.
Abstract:
Provided is an atypical environment-based location recognition apparatus. The apparatus includes a sensing information acquisition unit configured to, from sensing data collected by sensor modules, detect object location information and semantic label information of a video image and detect an event in the video image; a walk navigation information provision unit configured to acquire user movement information; a metric map generation module configured to generate a video odometric map using sensing data collected through a sensing information acquisition unit and reflect the semantic label information; and a topology map generation module configured to generate a topology node using sensing data acquired through the sensing information acquisition unit and update the topology node through the collected user movement information.
Abstract:
Provided is a multi-agent based manned-unmanned collaboration system including: a plurality of autonomous driving robots configured to form a mesh network with neighboring autonomous driving robots, acquire visual information for generating situation recognition and spatial map information, and acquire distance information from the neighboring autonomous driving robots to generate location information in real time; a collaborative agent configured to construct location positioning information of a collaboration object, target recognition information, and spatial map information from the visual information, the location information, and the distance information collected from the autonomous driving robots, and provide information for supporting battlefield situational recognition, threat determination, and command decision using the generated spatial map information and the generated location information of the autonomous driving robot; and a plurality of smart helmets configured to display the location positioning information of the collaboration object, the target recognition information, and the spatial map information constructed through the collaborative agent and present the pieces of information to wearers.
Abstract:
Provided herein is a link management method and apparatus in a multi-layered network, the method including confirming whether or not set virtual TE link resources can be committed to a virtual TE (traffic engineering) link; in response to the set virtual TE link resources being committable to the virtual TE link, committing the resources to the virtual TE link through resource commitment; in response to the set virtual TE link resources being not committable to the virtual TE link, determining whether or not the virtual TE link is an adaptive virtual TE link; and in response to the virtual TE link being determined as the adaptive virtual TE link and the adaptive bandwidth satisfying TE link setting standards, committing the resources to the virtual TE link.