Abstract: Systems and techniques are provided for calibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images captured by an extrinsic calibration tool to extract from the images, a three-dimensional (3D) point cloud of points corresponding to displays or structures that remain substantially immobile in the real space, and a second processing of a second set of images captured by a camera installation in the real space to match points in the second set of images to the point cloud. Differences in position of matching points can be used to determine transformation information therebetween, which can be used to calibrate the installed cameras.

Abstract: Techniques for managing coverage constraints are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: Automated techniques provide for recalibrating cameras configured for monitoring an area of real space. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. Transformation information between the selected images and the set of calibration images is obtained based on one or more features extracted from the selected images using a trained neural network classifier corresponding to points located at relatively immobile structures. The features extracted from the selected images match features in the set of calibration images. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: Exemplary embodiments in desalination by direct contact membrane distillation present a cylindrical cross-flow module containing high-flux composite hydrophobic hollow fiber membranes. The present embodiments are directed to a model that has been developed to describe the observed water production rates of such devices in multiple brine feed introduction configurations. The model describes the observed water vapor production rates for different feed brine temperatures at various feed brine flow rates. The model flux predictions have been explored over a range of hollow fiber lengths to compare the present results with those obtained earlier from rectangular modules which had significantly shorter hollow fibers.

Abstract: Automated techniques provide for recalibrating cameras in a real space in which puts and takes of items are tracked. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to match one or more features from the selected images with features extracted from the set of calibration images using a trained neural network classifier. The features correspond to points located at displays or structures that remain substantially immobile. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: Embodiments of the present disclosure provide an indoor positioning method for measuring a location of a mobile terminal using the mobile terminal and a plurality of positioning sensors communicating therewith. The indoor positioning method includes selecting a period for acquiring sensor information related to a relationship between the mobile terminal and the positioning sensors; acquiring a variable group corresponding to a positioning sensor selected from among the plurality of positioning sensors for each of unit periods of the selected period, the sensor information being acquired from the plurality of positioning sensors; applying a probability inference method to the variable group; and acquiring a final location of the mobile terminal based on the probability inference method, wherein the sensor information comprises signal strengths received by the mobile terminal from the positioning sensors, and a unique identification of the positioning sensors.

Abstract: The present invention provides a parking recognition method, which includes: acquiring a plurality of images photographed by one or more cameras, in relation to the at least one parking surface and the vehicle; determining a parking recognition time point as well as a corresponding camera for parking recognition (“a parking recognition camera”) among the one or more cameras, based on a difference in images between the time-sequentially continued plural images; setting a parking surface occupying-judgment area for the at least one parking surface, based on images photographed by the parking recognition camera at the parking recognition time point; setting a vehicle recognition area for based on the images photographed by the parking recognition camera at the parking recognition time point; and determining whether the vehicle is parked on the at least one parking surface, based on the parking surface occupying-judgment area and the vehicle recognition area.

Abstract: The technology disclosed relates to detecting events and identifying items in detected events in an area of real space in a shopping store including a cashier-less checkout system. The system comprises an image sensor assembly comprising at least one narrow field of view (NFOV) image sensor and at least one wide field of view (WFOV) image sensor. The at least one NFOV image sensor produces raw image data of first-resolution frames of a corresponding field of view and the at least one WFOV image sensor produces raw image data of second-resolution frames of a corresponding field of view. The system comprises logic to provide at least a portion of a sequence of second-resolution frames produced by the WFOV image sensor to an event detection device configured to detect (i) a particular event and (ii) a location of the particular event in the area of real space.

Abstract: Techniques for managing coverage constraints are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: A screen display method depending upon one embodiment of the present invention comprises: a step for setting, for an indoor space, depending upon a preset rule on a movement path on which a moving object can move, node data comprising information about the location of a positioning sensor; a first display step for, on the basis of first positioning data of a first point of the moving object, generating and displaying a first correction UI moving in a first direction in which the moving object moves, the first correction UI being displayed in a corrected speed compared to the actual speed of the moving object from a first start node to a first end node; and a step for determining a succeeding display step by determining whether the moving object rotates at the first end node.

Abstract: A method for indoor positioning, depending upon an embodiment of the present invention, comprises the steps of: setting node data including information regarding the location of a positioning sensor on a movement path of a moving object with respect to an indoor space; obtaining first positioning data capable of determining a first section in which the moving object is currently located, by using at least one of the node data, first sensing data obtained through a sensor unit provided in the moving object, and second sensing data obtained through the positioning sensor; determining whether the first positioning data satisfies a preset reference value for a boundary node defining the first section; and determining subsequent positioning data of the first positioning data on the basis of at least one of the node data, information indicating whether the reference value is satisfied, and information indicating whether the boundary node rotates.

Abstract: Exemplary embodiments in desalination by direct contact membrane distillation present a cylindrical cross-flow module containing high-flux composite hydrophobic hollow fiber membranes. The present embodiments are directed to a model that has been developed to describe the observed water production rates of such devices in multiple brine feed introduction configurations. The model describes the observed water vapor production rates for different feed brine temperatures at various feed brine flow rates. The model flux predictions have been explored over a range of hollow fiber lengths to compare the present results with those obtained earlier from rectangular modules which had significantly shorter hollow fibers.

Abstract: Exemplary embodiments in desalination by direct contact membrane distillation present a cylindrical cross-flow module containing high-flux composite hydrophobic hollow fiber membranes. The present embodiments are directed to a model that has been developed to describe the observed water production rates of such devices in multiple brine feed introduction configurations. The model describes the observed water vapor production rates for different feed brine temperatures at various feed brine flow rates. The model flux predictions have been explored over a range of hollow fiber lengths to compare the present results with those obtained earlier from rectangular modules which had significantly shorter hollow fibers.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: Automated techniques provide for recalibrating cameras in a real space in which puts and takes of items are tracked. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to match one or more features from the selected images with features extracted from the set of calibration images using a trained neural network classifier. The features correspond to points located at displays or structures that remain substantially immobile. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: Systems and techniques are provided for calibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images captured by an extrinsic calibration tool to extract from the images, a three-dimensional (3D) point cloud of points corresponding to displays or structures that remain substantially immobile in the real space, and a second processing of a second set of images captured by a camera installation in the real space to match points in the second set of images to the point cloud. Differences in position of matching points can be used to determine transformation information therebetween, which can be used to calibrate the installed cameras.

Abstract: Methods and systems for providing reward based verified recommendations. A method disclosed herein includes broadcasting a recommendation request to a plurality of registered users, on receiving the recommendation request from a customer. The method further includes receiving and verifying an input from at least user of the plurality of users in response to the broadcasted recommendation request using a blockchain. The received input relates to the recommendation request and the input includes at least one of at least one service provider and at least one service provided by the at least one service provider. The method also includes issuing reward points (RPs) to the at least one user who has provided the input and the service provider who is included in the input on verifying the input. The method further includes providing at least one recommendation to the requested customer using the verified input and maintained previous recommendations.

Abstract: Systems and techniques are provided for recalibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to extract a plurality of feature descriptors from the images. The first processing also includes a process step to match one or more feature descriptors as extracted from the selected images with feature descriptors extracted from the set of calibration images that were used to calibrate the cameras previously. The feature descriptors correspond to points located at displays or structures that remain substantially immobile.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.