Abstract: An electrostatic actuator includes a fixed electrode and a movable electrode arranged to face the fixed electrode. The movable electrode is configured to be displaceable with respect to the fixed electrode and a fixed portion. An attractive force acts between the movable electrode and the fixed portion. In the electrostatic actuator, a non-linear vibration of the movable electrode when a voltage is applied to the fixed electrode and the movable electrode is reduced by the attractive force acting between the movable electrode and the fixed portion.

Abstract: An image recognition device sets an overall observation region which surrounds a whole body of an object and partial observation regions which surround characteristic parts of the object respectively to locations in an image which are estimated to include captured images of the object. The device clips images in the overall observation region and the partial observation regions, and calculates similarity degrees between them and previously learned images on the basis of a combination of two image feature amounts. The device calculates an optimum ratio in combining the HOG feature amount and the color distribution feature amount individually for the regions. This ratio is determined by setting a weight parameter ?i for setting a weight used for combining the HOG feature amount and the color distribution feature amount to be included in a state vector and subjecting the result to complete search by a particle filter.

Abstract: An electronic device includes first and second controllers that execute processing based on first and second operating systems (OSes). The first controller includes a command generation unit that generates a command to be executed by the second controller, and a command transmission unit that includes a correspondence relationship associating in advance plural commands to be executed by the second controller with a control code stipulating an execution sequence of the plural commands, and if a control code corresponding to plural commands generated by the command generation unit exists in the correspondence relationship, the command transmission unit assigns the control code to the plural commands and transmits to the second controller. The second-controller receives the plural commands transmitted from the command transmission unit, and executes the plural commands based on the execution sequence stipulated by the assigned control code.

Abstract: An image recognition device adds a margin region filled with predetermined image data to a periphery of a captured image captured by a camera to create an expanded image larger than the captured image. When a person is too close to the camera, a part of a person image protrudes from the captured image, but a large detection window which also includes the margin region is set, whereby a window image including a protruding region is taken out of the expanded image. The window image lacks a protruding part of the person image, but it is an image showing an entire body of the person image. The image recognition device stores many reference images assuming various states of a person. The image recognition device extracts features from the window image, and compares them with a feature of the reference image, thereby recognizing the person image.

Abstract: An image recognition device includes: an image processing device that acquires a feature amount from an image; and an identification device that determines whether a prescribed identification object is present in the image, and identifies the identification object. The identification device includes a BNN that has learned the identification object in advance, and performs identification processing by performing a binary calculation with the BNN on the feature amount acquired by the image processing device. Then, the identification device selects a portion effective for identification from among high-dimensional feature amounts output by the image processing device to reduce the dimensions used in identification processing, and copies low-dimensional feature amounts output by the image processing device to increase dimensions.

Abstract: An image recognition device includes: an image processing device that acquires a feature amount from an image; and an identification device that determines whether a prescribed identification object is present in the image, and identifies the identification object. The identification device includes a BNN that has learned the identification object in advance, and performs identification processing by performing a binary calculation with the BNN on the feature amount acquired by the image processing device. Then, the identification device selects a portion effective for identification from among high-dimensional feature amounts output by the image processing device to reduce the dimensions used in identification processing, and copies low-dimensional feature amounts output by the image processing device to increase dimensions.

Abstract: A spatio-temporal image recognition device includes spatio-temporal image data generation units for converting moving-image data which continuously holds spatial information and temporal information to spatio-temporal image data, and they scan the moving-image data on scanning paths different from each other. The spatio-temporal image data generation units generate spatio-temporal image data scanned on the scanning paths different from each other and output them to an image recognition unit. The image recognition unit generates two-dimensional feature maps by individual convolution process of the spatio-temporal image data and then, integrates them, analyzes them by a neural network, and outputs an image recognition result.

Abstract: Method for controlling input to a touch panel includes a monitor screen display displaying a rear camera image screen, a measurement screen at the touch panel, and an input operation screen display in which an input operation can be performed. When the machine is operable, a monitor screen can be displayed in an input lock state in which the input operation is inhibited by turning off a hydraulic lock switch and releasing a hydraulic lock state. A specific input lock releasing operation on the touch panel releases the lock and the monitor screen display is switched to the input operation screen display.

Abstract: An image recognition device executes a Hilbert scan of frame image data constituting moving-image data to generate one-dimensional spatial image data, and further arrays the one-dimensional spatial image data in a time direction to generate two-dimensional spatio-temporal image data that holds spatial information and temporal information. The image recognition device converts the moving-image data into the two-dimensional spatio-temporal image data while holding the spatial and temporal information. By means of a CNN unit, the image recognition device executes a convolution process wherein a two-dimensional filter is used on the spatio-temporal image data to image-recognize a behavior of a pedestrian who is a recognition object.

Abstract: An image recognition device sets an overall observation region which surrounds a whole body of an object and partial observation regions which surround characteristic parts of the object respectively to locations in an image which are estimated to include captured images of the object. The device clips images in the overall observation region and the partial observation regions, and calculates similarity degrees between them and previously learned images on the basis of a combination of two image feature amounts. The device calculates an optimum ratio in combining the HOG feature amount and the color distribution feature amount individually for the regions. This ratio is determined by setting a weight parameter ?i for setting a weight used for combining the HOG feature amount and the color distribution feature amount to be included in a state vector and subjecting the result to complete search by a particle filter.

Abstract: A pulse wave detection device color converts a frame image of a moving image from RBG components to YIQ components, and identifies an eye section using the eye color of a user prepared in advance with a Q component. Next, the pulse wave detection device uses the Y values of the eye section to detect the brightness of the imaging environment. Then, the pulse wave detection device detects a pulse wave signal Qm on the basis of the average of the Q-values of a skin section in the frame image, corrects a change in the brightness by subtracting from Qm the average value Ye of the Y values of the eye section, and thereby outputs a post-brightness-correction Qm. As a result, a pulse wave can be successfully detected even if the brightness is changing because the user is moving in a vehicle or the like.

Abstract: An image processing device has a function for plotting a luminance gradient co-occurrence pair of an image on a feature plane and applying an EM algorithm to form a GMM. The device learns a pedestrian image and creates a GMM, subsequently learns a background image and creates a GMM, and calculates a difference between the two and generates a GMM for relearning based on the calculation. The device plots a sample that conforms to the GMM for relearning on the feature plane by applying an inverse function theorem. The device forms a GMM that represents the distribution of samples at a designated mixed number and thereby forms a standard GMM that serves as a standard for image recognition. When this mixed number is set to less than a mixed number designated earlier, the dimensions with which an image is analyzed are reduced, making it possible to reduce calculation costs.

Abstract: An image processing device converts an image that is a recognition object image to high-resolution, medium-resolution, and low-resolution images. The device sets the pixel of interest of the high-resolution image, and votes the co-occurrence in a gradient direction with offset pixels, the co-occurrence in the gradient direction pixels in the medium-resolution image, and the co-occurrence in the gradient direction pixels in the low-resolution image, to a co-occurrence matrix. The device creates such a co-occurrence matrix for each pixel combination and for each resolution. The device executes the process on each of the pixels of the high-resolution image, and creates a co-occurrence histogram wherein the elements of a plurality of co-occurrence matrices are arranged in a line. The device normalizes the co-occurrence histogram and extracts, as a feature quantity of the image, a vector quantity having as a component a frequency resulting from the normalization.

Abstract: A pulse wave detection device color converts a frame image of a moving image from RBG to HSV components, and identifies a skin section using the skin color of a user prepared in advance with an H component. The device converts the skin section of the image to YIQ components, and takes Qm as a pulse wave signal, Qm being obtained by averaging the Q values of the pixels. The device then obtains a chronological change in the pulse wave signal Qm and outputs the change as a pulse wave. Accordingly, it is possible to exclude disturbance factors from the pulse wave detection target, and successfully detect a pulse wave. The identification of the skin section is performed using the H component to identify candidate pixels, and using the S component to narrow down the candidate pixels to the target, so high-precision identification of the skin section is possible.

Abstract: An image recognition device adds a margin region filled with predetermined image data to a periphery of a captured image captured by a camera to create an expanded image larger than the captured image. When a person is too close to the camera, a part of a person image protrudes from the captured image, but a large detection window which also includes the margin region is set, whereby a window image including a protruding region is taken out of the expanded image. The window image lacks a protruding part of the person image, but it is an image showing an entire body of the person image. The image recognition device stores many reference images assuming various states of a person. The image recognition device extracts features from the window image, and compares them with a feature of the reference image, thereby recognizing the person image.

Abstract: A hardware configuration is constructed for calculating at high speed the co-occurrence of luminance gradient directions between differing resolutions for a subject image. In an image processing device, a processing line for high-resolution images, a processing line for medium-resolution images, and a processing line for low-resolution images are arranged in parallel, and the luminance gradient directions are extracted for each pixel simultaneously in parallel from images having the three resolutions. Co-occurrence matrix preparation units prepare co-occurrence matrices by using the luminance gradient directions extracted from these images having the three resolutions, and a histogram preparation unit outputs a histogram as an MRCoHOG feature amount by using these matrices. To concurrently processing the images having the three resolutions, high-speed processing can be performed, and moving pictures output from a camera can be processed in real time.

Abstract: A stator core, a stepper motor and a linear actuator allowing size reduction while maintaining a rotor diameter are provided. A stepper motor 1 comprises a rotor 20 and a stator 30, wherein the stator 30 comprises an A-phase magnetic pole part 33, a B-phase magnetic pole part 34 and a dummy magnetic pole part 38, all of which are disposed to be spaced apart from and opposing the outer circumferential surface of the rotor 20. The dummy magnetic pole part has no winding core part, and the A-phase magnetic pole part 33 and the B-phase magnetic pole part 34, which the stator 30 comprises, are disposed so that the A-phase magnetic pole part 33 and the B-phase magnetic pole part 34 are included within a minimum rectangular area R surrounding the rotor 20 when the stator 30 is viewed from a width direction X, i.e., a direction perpendicular to an axial direction P of the rotor 20.

Abstract: A pulse wave detection device color converts a frame image of a moving image from RBG components to YIQ components, and identifies an eye section using the eye color of a user prepared in advance with a Q component. Next, the pulse wave detection device uses the Y values of the eye section to detect the brightness of the imaging environment. Then, the pulse wave detection device detects a pulse wave signal Qm on the basis of the average of the Q-values of a skin section in the frame image, corrects a change in the brightness by subtracting from Qm the average value Ye of the Y values of the eye section, and thereby outputs a post-brightness-correction Qm. As a result, a pulse wave can be successfully detected even if the brightness is changing because the user is moving in a vehicle or the like.

Abstract: An electronic device includes first and second controllers that execute processing based on first and second operating systems (OSes). The first controller includes a command generation unit that generates a command to be executed by the second controller, and a command transmission unit that includes a correspondence relationship associating in advance plural commands to be executed by the second controller with a control code stipulating an execution sequence of the plural commands, and if a control code corresponding to plural commands generated by the command generation unit exists in the correspondence relationship, the command transmission unit assigns the control code to the plural commands and transmits to the second controller. The second-controller receives the plural commands transmitted from the command transmission unit, and executes the plural commands based on the execution sequence stipulated by the assigned control code.