Abstract:
Edges of layers are detected from an input image to create a boundary line candidate image that represents the detected edges. A luminance value of the input image is differentiated to create a luminance value-differentiated image that represents luminance gradient of the layers. An evaluation score image is created which is obtained by weighting calculation at an optimum ratio between a boundary line position probability image and the luminance value-differentiated image. The boundary line position probability image is obtained from the boundary line candidate image and an existence probability image that represents existence of a boundary line to be extracted. A route having the highest total evaluation score is extracted as the boundary line. According to such an image processing apparatus and image processing method, boundary lines of layers can be extracted with a high degree of accuracy from a captured image of a target object composed of a plurality of layers.
Abstract:
The image processing apparatus includes a boundary line extraction means that extracts a boundary line of a layer from an input image obtained by capturing an image of a target object composed of a plurality of layers. The boundary line extraction means is configured to first extract boundary lines at upper and lower ends of the target object, limit a search range using the extracted boundary lines at the upper and lower ends to extract another boundary line, limit the search range using an extraction result of the other boundary line to extract still another boundary line, and then sequentially repeat similar processes to extract subsequent boundary lines. In another aspect, the image processing apparatus includes a boundary line extraction means that extracts a boundary line of a layer from an input image obtained by capturing an image of a target object composed of a plurality of layers and a search range setting means that utilizes an already extracted boundary line extracted by the boundary line extraction means to dynamically set a search range for another boundary line. According to such an image processing apparatus and image processing method, boundary lines of layers can be extracted with a high degree of accuracy from a captured image of a target object composed of a plurality of layers.
Abstract:
A bioinformation acquiring apparatus includes at least one processor and a memory configured to store a program to be executed in the processor. The processor acquires a waveform signal representing vibrations of a target, the vibrations resulting from heartbeats of the target; extracts provisional heartbeat timings from the acquired waveform signal based on a first time window; the provisional heartbeat timings indicating provisional values of heartbeat timings being timings at which the heartbeats of the target occur; acquires corrective peak timings from the acquired waveform signal based on a second time window having a shorter time length than the first time window, each of the corrective peak timings serving as a discrete correction unit for correction of the provisional heartbeat timings; corrects the extracted provisional heartbeat timings into definitive heartbeat timings based on the acquired corrective peak timings; and acquires bioinformation on the heartbeats of the target based on the corrected heartbeat timings.
Abstract:
A sleep stage estimation device includes a subject data acquisition unit that acquires pulsation data and body movement data of a subject, a sleep stage probability estimation unit that acquires a feature quantity sequence from the pulsation data and estimates a sleep stage probability sequence of the subject from the acquired feature quantity sequence by using a learned sleep stage probability estimation model, a sleep stage transition probability estimation unit that acquires a body movement amount sequence from the body movement data and estimates a sleep stage transition probability sequence of the subject from the acquired body movement amount sequence by using a learned sleep stage transition probability estimation model, and a sleep stage estimation unit that estimates a sleep stage sequence of the subject from the sleep stage probability sequence and the sleep stage transition probability sequence by using a learned conditional random field model.
Abstract:
A cyclic alternative pattern (CAP) detection device includes a memory storing a program, and at least one processor configured to execute the program stored in the memory, in which the processor is configured to: acquire pulse wave data of a subject; derive a baseline of the pulse wave data and an envelope of the baseline; identify a local maximum point of the envelope and determine, as CAP candidate points each indicating a cyclic alternative pattern, a first local maximum point of the baseline before the local maximum point of the envelope and a second local maximum point of the baseline after the local maximum point of the envelope on a time axis; and identify, for each of the identified CAP candidate points, a third local maximum point of the baseline before the CAP candidate point and a local minimum point of the baseline between the CAP candidate point and the third local maximum point and detect the CAP candidate point as a CAP based on an evaluation value obtained from a difference between the CAP candidate point and the third local maximum point and a difference between the CAP candidate point and the local minimum point.
Abstract:
An autonomous movement device includes an obstacle detector, a map creator, an obstacle canceller, and a router. The obstacle detector detects an obstacle. The map creator records information about the obstacle detected by the obstacle detector on an environment map. The obstacle canceller cancels the information about the obstacle recorded by the map creator from the environment map. The router sets a moving route based on the information recorded on the environment map.
Abstract:
An image correction apparatus for correcting distortion of an image, the image being obtained by photographing a subject, which is provided with a specifying unit for specifying a relationship in position between points on the subject in a three-dimensional space based on both a relationship in position between the points on the subject in the image in a two-dimensional space and a photographing angle relative to a surface of the subject, an obtaining unit for obtaining information of distortion of the image that is reflected by the relationship in position between the points on the subject in the three-dimensional space, specified by the specifying unit, and a correcting unit for correcting the distortion of the image based on the information of distortion of the image obtained by the obtaining unit.
Abstract:
A state estimation apparatus includes: at least one processor; and a memory configured to store a program executable by the at least one processor; wherein the at least one processor is configured to: acquire a biological signal of a subject, in a certain period in which the biological signal is being acquired, set as a plurality of extraction time windows a plurality of time windows having mutually different time lengths, extract a feature value of the biological signal in each of the plurality time windows, and estimate a state of the subject based on the extracted feature value.
Abstract:
An aspect of the disclosure relates to a training device including a memory storing a program, and at least one processor configured to execute the program stored in the memory, in which the processor is configured to acquire pulse wave data to which biological reaction information is imparted, extract a local maximum point of a baseline or a local minimum point of a baseline derived from the pulse wave data as an identification reference point and set a correct answer label for the identification reference point based on the biological reaction information, set an analysis window for the extracted identification reference point and determine a feature vector of the identification reference point in the analysis window, and train a discriminator that identifies a cyclic alternating pattern (CAP) indicating a periodic brain wave activity by training data including the feature vector and the correct answer label.
Abstract:
A bioinformation acquiring apparatus includes at least one processor; and a memory configured to store a program to be executed in the processor. The processor acquires bioinformation in a chronological order; derives outlier level parameters, the outlier level parameter indicating a level of inclusion of outliers of the bioinformation in pieces of bioinformation acquired within a first duration; derives correction terms based on the bioinformation after removal of the outliers of the bioinformation from pieces of bioinformation acquired within a second duration that is longer than the first duration; selects one or both of a first correction procedure and a second correction procedure based on the outlier level parameters, as a correction procedure, the first correction procedure using the correction terms, the second correction procedure involving interpolation irrelevant to the correction terms; and corrects the outliers of the bioinformation within the first duration by the selected correction procedure.