54 results about "Volume estimation" patented technology

The invention discloses a crowd density estimation method based on video analysis and a pedestrian volume statistical method based on the video analysis. The crowd density estimation method includes the flowing steps of (1) off-line training: manually counting crowd density data, extracting characteristics and conducting training; and (2) on-line estimating: extracting the characteristics and conducting regression prediction by utilizing trained model parameters. The pedestrian volume statistical method includes the step of setting up a robust relationship between a scene and a line-passing number of people by combing the crowd density and a micro-region pedestrian flow speed before a line is passed. Characteristics such as foregrounds, edges and gray scale co-occurrence matrixes are extracted based on a whole area to conduct crowd density estimation, problems of dense crowds, sheltering and the like can be well solved through mixing of the characteristics, and real-time crowd density estimation is achieved. In addition, on the basis of area crowd density estimation, pedestrian volume estimation is conducted through combination of the pedestrian flow speed based on an optical flow, detection and tracking of a large number of individuals under a complex environment are avoided, and two-way pedestrian volume counting of accurate robust under dense crowds is achieved.

A system configured to estimate a change in temperature of a brake component of a vehicle brake during a braking operation. The system includes a weight estimation module for estimating a weight of a vehicle to which a brake is fitted, a volume estimation module for estimating a volume of a brake component, a temperature model module for calculating a change in temperature during brake application based on a relationship between the weight of the vehicle as estimated by the weight estimation module, the volume of the brake component as estimated by the volume estimation module, the deceleration of the vehicle, and further constants of the vehicle and / or the brake.

What is disclosed is a system and method for estimating tidal chest volume using 3D surface reconstruction based on an analysis of captured reflections of structured illumination patterns from the subject with a video camera. The imaging system hereof captures the reflection of the light patterns from a target area of the subject's thoracic region. The captured information produces a depth map and a volume is estimated from the resulting 3D map. The teachings hereof provide a non-contact approach to patient respiration monitoring that is particularly useful for infant care in a neo-natal intensive care unit (NICU), and can aid in the early detection of sudden deterioration of physiological condition due to detectable changes in respiratory function. The systems and methods disclosed herein provide an effective tool for tidal chest volume study and respiratory function analysis.

What is disclosed is a system and method for estimating tidal chest volume using 3D surface reconstruction based on an analysis of captured reflections of structured illumination patterns from the subject with a video camera. The imaging system hereof captures the reflection of the light patterns from a target area of the subject's thoracic region. The captured information produces a depth map and a volume is estimated from the resulting 3D map. The teachings hereof provide a non-contact approach to patient respiration monitoring that is particularly useful for infant care in a neo-natal intensive care unit (NICU), and can aid in the early detection of sudden deterioration of physiological condition due to detectable changes in respiratory function. The systems and methods disclosed herein provide an effective tool for tidal chest volume study and respiratory function analysis.

A refrigerator (50) provided with: a storage compartment for storing storage items, the compartment being partitioned by an insulating wall and an insulating door; a storage volume estimation unit (23) for estimating the storage volume of the storage compartment; and a memory unit (64) for recording the estimation result of the storage volume estimation unit (23). The refrigerator is further provided with a calculation controller (22) for calculating a storage change volume on the basis of the previous estimation result of the storage volume recorded in the memory unit (64) and the estimation result of the storage volume estimation unit, and controlling the output operation of electrical function components. The calculation controller (22) compares a preset threshold and the storage change volume, determines that the storage volume has changed when the storage change volume exceeds the threshold, and controls the output operation of the electrical function components.

An overlap identifying unit (205) obtains respective directions of the sound emitting objects with respect to the hearing position and identifies each one of sound emitting objects whose directions overlap. A sound volume estimation unit (206) estimates respective sound volumes of sounds as heard at the hearing position, emitted from the sound emitting objects that the overlap identification unit identified as overlapping. A sound emission control unit (207) cancels the sound emission of either one of the identified sound emitting objects identified, in a case where a difference between sound volumes obtained from those respective sound volumes estimated by the sound volume estimation unit (206) is at a predetermined level or greater. A sound source (208) reproduces sound effects or the like of the predetermined volumes. A game sound output unit (209) suitably outputs the game sound reproduced from the sound source (208).

A wound therapy system includes a negative pressure circuit configured to apply negative pressure to a wound, a pump fluidly coupled to the negative pressure circuit and operable to control the negative pressure within the negative pressure circuit, a pressure sensor configured to measure the negative pressure within the negative pressure circuit or at the wound and a controller communicably coupled to the pump and the pressure sensor. The controller is configured to execute a pressure testing procedure including applying a pressure stimulus to the negative pressure circuit, observe a dynamic pressure response of the negative pressure circuit to the pressure stimulus using pressure measurements recorded by the pressure sensor, and estimate a wound volume of the wound based on the dynamic pressure response.

What is disclosed is a wireless cellular device capable of determining a volume of an object in an image captured by a camera of that apparatus. In one embodiment, the present wireless cellular device comprises an illuminator for projecting a pattern of structured light with known spatial characteristics, and a camera for capturing images of an object for which a volume is to be estimated. The camera is sensitive to a wavelength range of the projected pattern of structured light. A spatial distortion is introduced by a reflection of the projected pattern off a surface of the object. And processor executing machine readable program instructions for performing the method of: receiving an image of the object from the camera; processing the image to generate a depth map; and estimating a volume of the object from the depth map. A method for using the present wireless cellular device is also provided.

The invention relates to the food field, in particular to a shell food freshness determination system based on a density model and a method of the system. A freshness weigher contains a two-dimensional code for software recognition, a groove for fixing food, a gradienter, a weighing disc for calculating the mass of the shell food and a positioning circle capable of estimating the size of the shell food. Freshness software (an APP, a wechat number, a microblog number and a cloude program) acquires an image through a phone camera under a normal daylight lamp (the illuminance is 100-160 Lux) and performs category recognition, mass recognition and size estimation of the shell food according to the acquired image. An automatic substituting and judging model has the advantage that intelligentilization, feedback real-time transformation and model control parameters can be updated in real time on the networking condition and is mainly used for real-time detection on the freshness of part of the shell food in daily life. Through resolving of the judging model set, a series of judging values and judging conclusions of the shell food freshness are obtained without needing to measure all specific indexes, and information is transmitted in real time. Judging results are judged through an indication interval with a certain confidence degree.

The invention provides a food volume estimation method based on double-view three-dimensional reconstruction. The method mainly comprises the steps of image 3D reconstruction, external calibration, dense reconstruction, and volume estimation. Particularly, the method comprises the steps of firstly performing image 3D reconstruction; performing external calibration through saliency point matching, relative gesture extraction and scale extraction; performing dense reconstruction through image correction, three-dimensional matching and point cloud generation; and finally eliminating background by means of a segmented graph and extracting a food surface, and calculating the volume of the food through integrating food surface height above a dish. According to the method of the invention, through acquiring the food image, the volume of the food is estimated through image reconstruction, thereby realizing convenient calculation process, high speed and accurate result. An accurate automatic meal evaluation tool is supplied for common groups and persons with specific nutrition requirements, and a novel full-automatic meal evaluation method for the people is realized.

An overlap identifying unit (205) obtains respective directions of the sound emitting objects with respect to the hearing position and identifies each one of sound emitting objects whose directions overlap. A sound volume estimation unit (206) estimates respective sound volumes of sounds as heard at the hearing position, emitted from the sound emitting objects that the overlap identification unit identified as overlapping. A sound emission control unit (207) cancels the sound emission of either one of the identified sound emitting objects identified, in a case where a difference between sound volumes obtained from those respective sound volumes estimated by the sound volume estimation unit (206) is at a predetermined level or greater. A sound source (208) reproduces sound effects or the like of the predetermined volumes. A game sound output unit (209) suitably outputs the game sound reproduced from the sound source (208).

The invention discloses a luggage volume automatic classification method based on a generative query network. The method comprises the following steps: (1) providing a scene image acquisition subsystem comprising a camera, a three-dimensional model generation subsystem comprising the generative query network, a scene segmentation subsystem and a luggage classification subsystem; (2) carrying out picture acquisition on the current actual scene containing the luggage through a camera; (3) taking the picture sequence obtained in the step (2) as input for generating a query network; (4) convertingthe three-dimensional model obtained in the step (3) into a point cloud file through a scene segmentation subsystem, and segmenting the point cloud file; and (5) calculating the volume of each pieceof luggage through a luggage classification subsystem according to the obtained point cloud data of each piece of luggage, and identifying each piece of luggage as a volume range where the volume of each piece of luggage is located. Due to the adoption of an artificial intelligence method, subsidy positioning and volume estimation can be realized without excessive manual intervention, and the method has wider applicability.

The invention provides an environment self-adaptation volume adjusting method and a digital television reception terminal. The method comprises the following steps: a digital television reception terminal determines a volume estimation value F0 (E, i) according to influences of a present environment noise value E and a present channel volume value i on volume, and obtains a time factor P influencing volume and a volume preference factor q influencing volume; the digital television reception terminal multiplies F0, p and a to obtain a multiply result; a digital television receives the multiplyresult which is taken as a volume value after adjustment. According to the invention, volume adjustment can be carried out with self-adaptation, and number of adjusting volume manually is reduced.

A method and an incontinence monitoring system for estimating a volume or a volume range of a bodily output in a combination absorbent article and wetness sensor. The system comprises a combination of an absorbent article and a wetness sensor, and a processor adapted to receive an input representative of an electrical variable of the wetness sensor indicative of the occurrence of a bodily output in the absorbent article and to process the input including: characterising the input to generate a vector that is representative of the bodily output, applying one or more functions to the vector to generate one or more possible volumes of the bodily output, generating a distribution of the possible volumes, and determining a volume or a volume range for the bodily output based on the distribution of the possible volumes.

The invention discloses a mixed effect model for predicting large-area subtropical forest biomass, belonging to the technical field of forest management and related to an extraction technology of forest biomass. By relatively convenient data acquisition approaches and relatively less capital and personnel investment, an extraction technology aiming at large-area subtropical forest biomass is designed. The technology is mainly composed of five stages including extraction of laser radar data feature variables, ground sample plot data stem volume estimation, model construction and model verification based on vegetational forms and biomass calculation based on the stem volume and a biomass relative growth model. The technology improves biomass estimation precision of a laser radar method in alarge-scale forest, and provides a simplified technical solution for an airborne laser radar in forestry reconnaissance application of a large-area subtropical forest.

A remediation process that a employs improved quantitative method(s) of estimating of the volume and / or mass of contaminant in the subsurface, removal and or in situ degradation of the contamination using subsurface pulsing treatment (“SPT”) technology, and evaluation of the degree of remediation by re-applying the quantitative contaminant evaluation methods. The process uses SPT technology with the addition of a vacuum or sub-atmospheric pressure to an extraction well in order to create a push-pull effect to remove free contaminant or residual in conjunction with the pressure wave driving force created in the excitation or excitation well. The process can quantitatively measure the amount of residual contaminant, which up until now has not been possible or tractable using in situ methods, as well as measure the amount of residual that can be removed by SPT.

The invention discloses a method and a device for determining the traffic travel volume of vehicles. The method comprises steps: travel data of vehicles in a set time are acquired; according to number information of traffic cells and the travel data of vehicles of the first type, the traffic travel volume corresponding to the travel data of vehicles of the first type and the number of a traffic cell at the starting point and the number of a traffic cell at the destination of the travel data of vehicles of the first type are determined; and according to the number information of the traffic cells and travel data of vehicles of the second type, the traffic travel volume corresponding to the travel data of vehicles of the second type and the number of a traffic cell at the starting point and the number of a traffic cell at the destination of the travel data of vehicles of the second type are determined, and thus, the traffic travel volume of vehicles is determined. Through acquiring the accurate travel data of vehicles of the first type and not using passing data acquired by the vehicles of the first type from a traffic monitoring system, and the vehicle traffic travel volume estimation accuracy can be improved.

The invention improves volume estimation accuracy of an object in a container using a captured image in a case where a blind spot region exists in a captured image of the object in the container. A blind spot estimation portion for estimating the blind spot region of the object in the bucket; a blind spot region shape estimation portion for estimating a shape of the object in the blind spot region; and a volume estimation portion for estimating a volume of the object in the blind spot region are included, the blind spot estimation portion estimates the blind spot region by mesh disparity data obtained from a captured image of the object in the bucket imaged by a plurality of cameras, the blind spot region shape estimation portion estimates the shape of the object in the blind spot region by the mesh disparity data, and the volume estimation portion estimates the volume of the object in the blind spot region based on the shape of the object in the blind spot region estimated by the blind spot region shape estimation portion and a shape of a bottom of the bucket.

The invention discloses a remote sensing-based landslide mass volume estimation method. The method is characterized by comprising the steps of obtaining a post-disaster remote sensing image and a pre-disaster terrain data DEM of a to-be-estimated landslide mass region; performing boundary extraction on the landslide mass region in the post-disaster remote sensing image, and extracting and obtaining feature points of a landslide mass boundary; selecting a reference plane; based on the feature points of the landslide mass boundary, performing surface fitting on a landslide mass to obtain a fitted landslide mass surface, and calculating the volume between the fitted landslide mass surface and the reference plane; according to the DEM, extracting an original terrain surface, and calculating the volume between the original terrain surface and the reference plane; and fitting a difference between the volume between the landslide mass surface and the reference plane, and the volume between the original terrain surface and the reference plane to serve as a landslide mass volume. According to the method, the estimation precision of the landslide mass volume can be improved, so that the estimation time is greatly shortened.

The present invention discloses a food volume estimation method based on 3D model nesting. The method can restore a simple geometric model corresponding to foods so as to solve the estimated volume ofthe foods. The method comprises the following steps of: selecting a special model to establish a three-dimensional model library, and inputting user hand information; putting the hand and the foods to the same plane for shooting to obtain a three-view image; performing L*a*b color space preprocessing of the image, performing k-means clustering segmentation of a processing result, and obtaining animage segmentation result; performing outer contour matching of the segmentation result and the three views of the model in the three-dimensional model library, and according to the special function,calculating the matching degree of the foods and each model projection map to find out a projection map having the maximum matching degree, wherein the three-dimensional model corresponding to the projection map having the maximum matching degree is a three-dimensional model corresponding to the foods; and taking the hand as a measuring scale to determine the parameters of the matching model so as to estimate the volumes of the foods through a volume calculation formula. The food volume estimation method based on 3D model nesting can simplify the volume reconfiguration complexity to estimatethe effect of food volumes.

The invention discloses a food volume estimation method and device and belongs to the technical field of deep learning. The method comprises the steps that image or video data containing multiple types of food is collected, and true volume data of the food in the collected image or video data is obtained; a preset deep learning neural network model is utilized to perform training according to theimage or video data and the true volume data, and a volume estimation model is obtained; and according to the image or video data of to-be-tested food, the volume estimation model is utilized to obtain a volume estimation result of the to-be-tested food. The volume estimation method is simple and efficient, a user can quickly obtain a predicted volume of the food simply by inputting a food image or a short food video, and the method can be widely applied to network information services like intelligent diet management requiring frequent and rapid food volume estimation.

The present invention is equipped with: a refrigeration device that cools the interior of storage compartments; dampers (67) that control the supplied amount of cold air generated by the refrigeration device, and that correspond to each storage chamber; and a calculation control unit (22) that performs calculations on the basis of input data from a storage volume estimation unit (23) and a memory unit (64), and that controls the refrigeration device. In addition, normally an energy conservation operation is performed by controlling the damper (67) corresponding to each storage chamber, and when the storage volume has changed greatly due to bulk buying or the like, the amount of cooling of a chamber for which the storage volume has changed is increased by controlling the dampers (67), thereby cooling the introduced storage items to the optimum preservation temperature in a short amount of time.

The invention relates to a bus passenger volume estimation method based on machine learning, and belongs to the fields of machine learning and intelligent traffic. A camera is erected in a bus to obtain a certain number of video images as training samples; the samples are marked, and an ROI probability density distribution map of each sample is calculated; the samples and the corresponding ROI probability density distribution maps are send to a deep convolutinal neural network for training to generate a model; and a video image to be detected is obtained, the model generated by training is used to regress an ROI probability density distribution map of the video image to be detected, all pixels in the ROI probability density distribution map are accumulated, and an accumulated value approximates to the passenger volume in the image to be detected. According to the method, disposition is easy, most time is spent in the machine learning stage, and in practical use, the trained model can be used directly, and passenger volume estimation is very low in computational complexity and high in computation speed.

The invention provides a volume estimation method of a building, which comprises the following steps of: carrying out aerial photography sampling and field sampling on the building to obtain a plurality of images of the building, and image preprocessing is carried out on the plurality of images; obtaining the original points, original edges and original faces of the buildings after image preprocessing, finding out the corresponding relations of the same points, edges and faces in any two images, and matching the obtained image sequences; calculating the actual distance between all the specificpoints in the three-dimensional model; calculating the volume of a building. The invention adds relative constraint to the reconstructed characteristic points according to the dispersion and disorderof the points, lines and planes of the building, obtains the ratio of the building in the relative coordinate system to the actual size of the building as the scale information, thereby completing the purpose of accurate and rapid volume estimation by utilizing the three-dimensional reconstruction of the building.

The invention provides a method for constructing a tree trunk volume estimation model, a volume estimation method and a system, wherein, method for constructing a tree trunk volume estimation model comprises the steps of three-dimensionally scanning individual trees, and sampling point cloud data of a tree trunk; conducting point cloud data preprocessing, including deleting redundant point cloud data outside the tree trunk; in the vertical direction, dividing the trunk point cloud data into n layers horizontally, and calculating the volume of each layer slice by the method of cross-sectional area integral, then the volume of n layers is superposed to obtain the volume of the whole tree trunk. The trunk volume model of trunk volume and trunk model factor was constructed by using the trunk model factor and the calculated volume result and linear regression analysis to fit the trunk model. Compared with the prior art, the invention reduces the destruction to the forest, improves the accuracy of modeling, and can realize the accurate modeling of irregular objects, the modeling workload is small, the time consuming is short, and the timeliness of modeling can be satisfied.

Described herein are methods, systems, apparatuses and products for determining relative criticality of service tickets in factory-style shared delivery. An aspect provides for accessing ticket information, accessing service level agreement information, accessing future volume estimation information, estimating a number of missed service level objectives that are permissible without having a service level agreement breach; and determining a criticality of at least one received ticket based on said ticket information, said service level agreement information, and said future volume estimation information. Other embodiments are disclosed.

The invention includes a system to determine body surface area (BSA) or volume of an animal that can be used to determine a health status of the animal. The system has a plurality of integrated measuring devices such as radar or infrared sensors. The measuring devices are mounted within a confined space. A plurality of measurements is taken along vertically oriented sections or slices of the animal as the animal passes by the confined space. The measurements are combined and numerically converted to BSA or volume estimations. The health status can be derived as a direct relation to BSA or volume, or changes in BSA or volume over a selected time period.

The invention relates to a transmission performance analysis system, and the system comprises a load analysis mechanism which is used for calculating the weight of a coal body corresponding to the solid volume of a three-dimensional region based on the density of the coal body and the solid volume of the three-dimensional area and outputting the weight of the coal body as the weight of a field coal body; a load analysis mechanism further used for sending out a power shortage signal when the received weight of the on-site coal body is larger than the weight of the coal body capable of being driven by the maximum output power of a conveyor belt; and volume estimation equipment used for estimating the solid volume of the three-dimensional area based on each geometric parameter of the simulated three-dimensional area. The transmission performance analysis system is stable in operation and reliable in data. Due to the fact that a targeted high-precision visual detection mechanism can be adopted for the obliquely-arranged conveyor belt facility to detect the total weight of the coal briquettes of the current load of the conveying belt, the load detection error is reduced.

A method and system for determining normalized metrics for visceral adipose tissue (VAT) mass and volume estimation. The normalized metrics including a VAT average cross-section determined by dividing a VAT volume by a height of the abdominal region of interest, and a VAT linear mass density determined by dividing the VAT mass by a height of an abdominal region of interest.