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:
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 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 are an apparatus, system, and method for providing a stereoscopic indoor route, which can effectively guide a route in consideration of various features and structures of the indoor space unlike an existing navigation performed on only the outdoor space, in order to provide a navigation service performed on the indoor space. For stereoscopic movement, such as going upstairs or downstairs in inter-floor movement, which is characteristic of the indoor space, it is also possible to effectively and efficiently provide route guidance to a user by indicating up and down directions with a special arrow or icon and visualizing a route with icons for facilities, such as a general door, a revolving door, an escalator, and an elevator, which are specialized in the indoor space.
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:
An apparatus for processing indoor geospatial information for an indoor location-based service and a method thereof are provided. The apparatus includes a registerer configured to classify and register indoor geospatial information according to conditions that include a structure of a building and features of indoor space, and provide a user terminal with access information regarding specific indoor geospatial information found by the user terminal; and a provider configured to provide indoor geospatial information to the user terminal that has accessed the provider using the access information regarding the indoor geospatial information.