Mitsubishi Electric Corporation

Mitsubishi Electric Research Laboratories, Inc.

Yudai Nakamura

Masahiro Naito

Masashi Kamiya

Takashi Hirano

Hassan Mansour

Tim Marks

Tomonori Fukuta

Ryosuke Torama

Ewa Nowara

Ashok Veeraraghavan

Takuya Murakami

Masanobu Osawa

Hisashi Sugawara

Nobuhiko Yamagishi

Natsuki Tahara

Kazuki Kunihiro

Daichi Tsunemichi

Taichi Kojima

Ashok Veeraghavan

A respiration information estimation device includes a specific region setting unit that sets a specific region and a motion vector calculation point as a point as a reference of a motion vector based on an image including an upper body of an object person, a motion vector calculation unit that calculates the motion vector from a movement amount of the motion vector calculation point in each of the images captured consecutively, a respiration reference axis calculation unit that calculates a respiration reference axis from a respiration central point and the motion vector calculation point, a respiration signal calculation unit that calculates a respiration signal from a component of the motion vector in a direction of the respiration reference axis, and a respiration information calculation unit that calculates a respiration information estimation result, as a result of estimating a body motion caused by the respiration, from the respiration signal.

Respiration information estimation device and respiration information estimation method

An eye tracking device according to the present disclosed technology includes: an image acquiring unit that acquires an image of a subject; an arithmetic processing unit that performs image processing; and a line-of-sight angle calculating unit that calculates a line-of-sight direction vector on the basis of a result of the image processing. The arithmetic processing unit includes: a real image arithmetic processing unit that performs arithmetic processing on a real image in an image space; and a three-dimensional model superimposition processing unit that performs superimposition processing on the image space using a three-dimensional face model. The three-dimensional model superimposition processing unit includes a three-dimensional model correcting unit that corrects the three-dimensional face model in order to eliminate an error caused by the superimposition processing.

Eye tracking device

A remote photoplethysmography (RPPG) system for estimating vital signs of a person is provided. The RPPG system is configured to receive a set of imaging photoplethysmography (iPPG) signals measured from different regions of a skin of a person. The RPPG system is further configured to determine frequency coefficients at the frequency bins of the quantized frequency spectrum of the measured iPPG signals by minimizing a distance between the measured iPPG signals and corresponding iPPG signals reconstructed from the determined frequency coefficients, while enforcing joint sparsity of the determined frequency coefficients subject to the sparsity level constraint, such that the determined frequency coefficients of different iPPG signals have the non-zero values at the same frequency bins; and output one or a combination of the determined frequency coefficients, the iPPG signals reconstructed from the determined frequency coefficients, and a vital sign signal corresponding to the reconstructed iPPG signals.

System and method for remote measurements of vital signs of a person in a volatile environment

A motion sickness estimation device including processing circuitry configured to calculate a sensory conflict amount on a basis of a motion of an occupant's head caused by vibration of a vehicle; extract a feature of a traveling situation on a basis of at least one of the motion of the occupant's head or a motion of the vehicle; determine a habituation progress state, which is a state in which the occupant's habituation to the traveling situation has progressed, on a basis of biometric information of the occupant; set sensitivity to the feature of the traveling situation on a basis of the habituation progress state; correct the sensory conflict amount on a basis of the sensitivity; and estimate a motion sickness state of the occupant on a basis of the sensory conflict amount that has been corrected.

Motion sickness estimation device, motion sickness reducing device and motion sickness estimation method

A remote photoplethysmography (RPPG) system includes an input interface to receive a sequence of measurements of intensities of different regions of a skin of a person indicative of vital signs of the person; a solver to solve an optimization problem to determine frequency coefficients of photoplethysmographic waveforms corresponding to the measured intensities at the different regions, wherein the solver determines the frequency coefficients to reduce a distance between intensities of the skin reconstructed from the frequency coefficients and the corresponding measured intensities of the skin while enforcing joint sparsity on the frequency coefficients; and an estimator to estimate the vital signs of the person from the determined frequency coefficients of photoplethysmographic waveforms.

System and method for remote measurements of vital signs

An area extraction unit () extracts an eye area in an image of a driver. An eyelid detection unit () detects an eyelid in the eye area. A reliability calculation unit () calculates an eyelid reliability by using luminance information of the eye area and positional information of the eyelid detected by the eyelid detection unit (). A determination unit () determines that the eyelid has not been properly detected, when the eyelid reliability is less than a first threshold value.

Determination apparatus and method to enhance accuracy in determining the presence of an erroneously detected eyelid

There are included: a frequency distribution creating unit for referring to the face information detected by the face information detecting unit, and when a preset change occurs in the driver's face, creating a frequency distribution of face information in a preset time section from the face information detected by a face information detecting unit; a mode value calculating unit for calculating a mode value of the face information from the frequency distribution created; and a reference value calculating unit for calculating a reference value indicating a steady state of the driver from the mode value of the face information.

Driving state determination device, determination device, and driving state determination method

A motion sickness estimation device includes: a line-of-sight oscillation detector to detect oscillation of a line of sight of an occupant by using an imaging device; an object oscillation detector to detect oscillation of an object located in the line of sight; an oscillation comparator to calculate an oscillation difference from the oscillation of the line of sight and the oscillation of the object; and a motion sickness determiner to determine, on a basis of the oscillation difference, whether the occupant is in a motion sickness state.

Motion sickness estimation device, motion sickness prevention device, and motion sickness estimation method

A gesture judgment device includes a reference part detection unit that outputs reference part information indicating a reference part region, a movement extraction unit that outputs movement information indicating a movement region, a reference part disappearance judgment unit that generates a reference part disappearance information, a timing judgment unit that judges whether first timing indicated by the reference part disappearance information and second timing of occurrence of a frame in which the movement region overlaps with the reference part region indicated by the reference part information are synchronized with each other or not and outputs a timing judgment result as the result of the judging, and an operation judgment unit that judges contents of a gesture operation performed by an operator based on the timing judgment result and the movement information.

Gesture judgment device, gesture operation device, and gesture judgment method

An eyelid detection device includes a face feature point detecting unit for detecting outer and inner eye corners as face feature points from a captured image, an eye region detecting unit for detecting an eye region including both an upper eyelid area and an eye area from the captured image on the basis of the face feature points, and an upper eyelid detecting unit for, for each of a plurality of divided areas into which the eye region is divided, detecting the boundary between the upper eyelid area and the eye area on the basis of the pattern of arrangement of the intensity values of pixels aligned in the divided region, and for connecting the boundary detected for each of the divided regions, to determine an upper eyelid.

Eyelid detection device, drowsiness determination device, and eyelid detection method

A luminance variation (dI) pertaining to each pixel is calculated () using a plurality of captured images obtained by image capturing under different illumination conditions, a texture variation (dF) pertaining to each pixel is calculated () using a plurality of captured images obtained by image capturing at different time points, and a subject region is extracted () based on the luminance variation (dI) and the texture variation (dF). A variation in the texture feature (F) pertaining to each pixel between the images is calculated as the texture variation (dF). The subject can be extracted with a high accuracy even when there are changes in the ambient light or the background.

Imaging apparatus and method, operation apparatus and method, and program and recording medium

Provided are a gesture recognition device, a gesture recognition method and an information processing device for making it possible to quickly recognize a gesture of a user. The gesture recognition device includes a motion information generator that generates body part motion information by performing detection and tracking of the body part, a prediction processor that makes a first comparison of comparing the generated body part motion information with previously stored pre-gesture motion model information and generates a prediction result regarding a pre-gesture motion on the basis of a result of the first comparison, and a recognition processor that makes a second comparison of comparing the generated body part motion information with previously stored gesture model information and generates a result of recognition of the gesture represented by a motion of the detected body part on the basis of the prediction result and a result of the second comparison.

Gesture recognition device, gesture recognition method, and information processing device

A hand region is detected in a captured image, and for each part of the background area, a light source presence degree indicating the probability that a light source is present is determined according to the luminance or color of that part; on the basis of the light source presence degree, a region in which the captured image is affected by a light source is estimated, and if the captured image includes a region estimated to be affected by a light source, whether or not a dropout has occurred in the hand region in the captured image is decided; on the basis of the result of this decision, an action is determined. Gesture determinations can be made correctly even when the hand region in the captured image is affected by a light source at the time of gesture manipulation input.

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Tokyo, Japan

Yudai Nakamura