Abstract: An electromagnetic contactor 1 includes a case including an arc extinguishing chamber, an arc extinguishing cover attached to the case and covering the arc extinguishing chamber, and terminal covers arranged on the arc extinguishing cover and attached to the case. The case is formed with a first engagement portion, and the terminal covers are formed with a second engagement portion that is engaged with the first engagement portion to hold the terminal covers on the case. Then, the terminal covers are held on the case in either a first state where there is a gap between the first and second engagement portions or a second state where the terminal covers move in directions away from the arc extinguishing cover and the first and second engagement portions are engaged.

Abstract: A driving assistance device acquires a surrounding area map, determines whether a subject vehicle is travelable in an assistance target scene based on the surrounding area map, generates a guide that guides the subject vehicle in the assistance target scene based on the surrounding area map, adjusts relative positions of an obstacle and the guide in the surrounding area map in accordance a reference position information, perform a steering assistance to assist steering of the subject vehicle in accordance with the guide when determines that the subject vehicle is travelable, and updates the reference position information in accordance with a degree of deviation between the guide and an actual trajectory along which the subject vehicle passes during the steering assistance.

Abstract: A finger mechanism for a robot, an artificial hand, and the like, wherein a fourth bone member (14) of the bone members of the finger mechanism and corresponding to the distal phalanx comprises: a support portion (15) that is rotatably coupled to a third bone member corresponding to the middle phalanx by a rotational shaft (g5); and a nail portion (16). The nail portion (16) can freely rotate about a shaft (g7) at a right angle or a near right angle to the rotational shaft (g5), and a return mechanism (17) to return the rotated nail portion (16) to a reference position is provided between the support portion (15) and the nail portion (16). In this manner, in response to the amount of force applied to the fourth bone member (14), it is possible for only the nail portion (16) to rotate in a direction to easily grasp an object to be held.

Abstract: This sheet for assembling a device includes: a movable mechanism body forming portion (200); a supporting body forming portion (400); and a connecting part forming portion (600) connecting and angle-adjustably holding the aforementioned bodies. The movable mechanism body forming portion includes: a base body forming portion (220) forming a base body with a bent portion; a drive body forming portion (240) disposed in parallel to the base body, forming a drive body with a bent portion; a bent portion connecting portion forming portion (260) connecting the base body and the drive body at the bent portions; and a movable mechanism base end portion forming portion (280) integrating the base body and the drive body at base ends. The supporting body forming portion includes a supporting body main body forming portion that forms a supporting body main body having a length corresponding to the movable mechanism portion.

Abstract: A finger mechanism for a robot, an artificial hand, and the like, wherein a fourth bone member (14) of the bone members of the finger mechanism and corresponding to the distal phalanx comprises: a support portion (15) that is rotatably coupled to a third bone member corresponding to the middle phalanx by a rotational shaft (g5); and a nail portion (16). The nail portion (16) can freely rotate about a shaft (g7) at a right angle or a near right angle to the rotational shaft (g5), and a return mechanism (17) to return the rotated nail portion (16) to a reference position is provided between the support portion (15) and the nail portion (16). In this manner, in response to the amount of force applied to the fourth bone member (14), it is possible for only the nail portion (16) to rotate in a direction to easily grasp an object to be held.

Abstract: A driving assistance device acquires a surrounding area map, determines whether a subject vehicle is travelable in an assistance target scene based on the surrounding area map, generates a guide that guides the subject vehicle in the assistance target scene based on the surrounding area map, adjusts relative positions of an obstacle and the guide in the surrounding area map in accordance a reference position information, perform a steering assistance to assist steering of the subject vehicle in accordance with the guide when determines that the subject vehicle is travelable, and updates the reference position information in accordance with a degree of deviation between the guide and an actual trajectory along which the subject vehicle passes during the steering assistance.

Abstract: In an apparatus, an applying unit applies selected classifiers in sequence to an object image. A score calculating unit calculates, each time a classifier is applied to the object image, a summation of an output of an at least one classifier already applied to the object image to thereby obtain an acquisition score as the summation. The output of the at least one already applied classifier is weighed by a corresponding weight. A distribution calculating unit calculates, each time a classifier is applied to the object image, a predicted distribution of the acquisition score that would be obtained if at least one unapplied classifier in the classifiers, which has not yet been applied to the object image, were applied to the object image. A judging unit judges, based on the predicted distribution, whether to terminate an application of the at least one unapplied classifier to the object image.

Abstract: The position of a face image within an input image is detected based on results from applying a plurality of weak classifiers in sequence to each of sub-images extracted from the input image. A decision whether to interrupt the sequence and reject a currently extracted sub-image is made based on the sum of a total of weighted decision values obtained up to the current point in the sequence and a total of potential weighted decision values obtainable from the remaining weak classifiers if the extracted sub-image were a face image.

Abstract: A face model providing portion provides an stored average face model to an estimation portion estimating an affine parameter for obtaining a head pose. An individual face model learning portion obtains a result of tracking feature points by the estimation portion and learns an individual face model. The individual face model learning portion terminates the learning when a free energy of the individual face model is over a free energy of the average face model, and switches a face model provided to the estimation portion from the average face model to the individual face model. While learning the individual face mode, an observation matrix is factorized using a reliability matrix showing reliability of each observation value forming the observation matrix with emphasis on the feature point having higher reliability.

Abstract: In an apparatus, an applying unit applies selected classifiers in sequence to an object image. A score calculating unit calculates, each time a classifier is applied to the object image, a summation of an output of an at least one classifier already applied to the object image to thereby obtain an acquisition score as the summation. The output of the at least one already applied classifier is weighed by a corresponding weight. A distribution calculating unit calculates, each time a classifier is applied to the object image, a predicted distribution of the acquisition score that would be obtained if at least one unapplied classifier in the classifiers, which has not yet been applied to the object image, were applied to the object image. A judging unit judges, based on the predicted distribution, whether to terminate an application of the at least one unapplied classifier to the object image.

Abstract: An estimation device estimates a hidden state of an estimation subject from an observable state in a manner of a time series. The observable state is observed from the hidden state of the estimation subject under a procedure that has a hierarchical structure, which includes the hidden state of the estimation subject, the observable state, and an intermediate hidden state therebetween. The estimation device includes an estimation subject hidden state predicting means, an intermediate hidden state predicting means based on the state transition structure of the hidden state of the estimation subject, an intermediate hidden state likelihood observing means, an intermediate hidden state estimating means, an estimation subject hidden state likelihood observing means, estimation subject hidden state estimating means, an intermediate hidden state predicting means based on the state transition structure of the intermediate hidden state, and the mixing means.

Abstract: An attention calling apparatus operates in the following manner. That is, eyes distribution pattern is generated from the behavior of the eyes of the vehicle driver captured by a camera in a predetermined time, and driver's condition is estimated based on the distribution pattern. Further, concentration of the driver on driving is estimated based on the comparison between the distribution pattern and the stored information of distribution pattern. When the distribution pattern indicates that the degree of concentration on driving is high, the driving operation is stored in storage in association with the concentration degree. When the operation situation fulfills a notification provision condition, driver's attention is called depending on the concentration degree.

Abstract: A method for detecting an ellipsoid includes: extracting an ellipsoid candidate; extracting an ellipsoid contour; calculating an ellipsoid parameter; calculating an adaptability ratio; and eliminating the ellipsoid candidate. Extracting the ellipsoid candidate includes: inputting an image with figures; selecting the ellipsoid candidate from the figures; and extracting a contour candidate point and a center point. Extracting the ellipsoid contour includes: drawing straight lines; determining contour candidate points; calculating first and second distances; and defining ellipsoid contour points. Calculating the ellipsoid parameter is based on the ellipsoid contour points and the center point. Calculating the adaptability ratio includes: drawing a complete ellipsoid; and calculating the adaptability ratio between the complete ellipsoid and the ellipsoid candidate. Eliminating the ellipsoid candidate is performed when the adaptability ratio is equal to or smaller than a threshold.

Abstract: The position of a face image within an input image is detected based on results from applying a plurality of weak classifiers in sequence to each of sub-images extracted from the input image. A decision whether to interrupt the sequence and reject a currently extracted sub-image is made based on the sum of a total of weighted decision values obtained up to the current point in the sequence and a total of potential weighted decision values obtainable from the remaining weak classifiers if the extracted sub-image were a face image.

Abstract: A face model providing portion provides an stored average face model to an estimation portion estimating an affine parameter for obtaining a head pose. An individual face model learning portion obtains a result of tracking feature points by the estimation portion and learns an individual face model. The individual face model learning portion terminates the learning when a free energy of the individual face model is over a free energy of the average face model, and switches a face model provided to the estimation portion from the average face model to the individual face model. While learning the individual face mode, an observation matrix is factorized using a reliability matrix showing reliability of each observation value forming the observation matrix with emphasis on the feature point having higher reliability.

Abstract: An attention calling apparatus operates in the following manner. That is, eyes distribution pattern is generated from the behavior of the eyes of the vehicle driver captured by a camera in a predetermined time, and driver's condition is estimated based on the distribution pattern. Further, concentration of the driver on driving is estimated based on the comparison between the distribution pattern and the stored information of distribution pattern. When the distribution pattern indicates that the degree of concentration on driving is high, the driving operation is stored in storage in association with the concentration degree. When the operation situation fulfills a notification provision condition, driver's attention is called depending on the concentration degree.

Abstract: An estimation device estimates a hidden state of an estimation subject from an observable state in a manner of a time series. The observable state is observed from the hidden state of the estimation subject under a procedure that has a hierarchical structure, which includes the hidden state of the estimation subject, the observable state, and an intermediate hidden state therebetween. The estimation device includes an estimation subject hidden state predicting means, an intermediate hidden state predicting means based on the state transition structure of the hidden state of the estimation subject, an intermediate hidden state likelihood observing means, an intermediate hidden state estimating means, an estimation subject hidden state likelihood observing means, estimation subject hidden state estimating means, an intermediate hidden state predicting means based on the state transition structure of the intermediate hidden state, and the mixing means.

Abstract: A method for detecting an ellipsoid includes: extracting an ellipsoid candidate; extracting an ellipsoid contour; calculating an ellipsoid parameter; calculating an adaptability ratio; and eliminating the ellipsoid candidate. Extracting the ellipsoid candidate includes: inputting an image with figures; selecting the ellipsoid candidate from the figures; and extracting a contour candidate point and a center point. Extracting the ellipsoid contour includes: drawing straight lines; determining contour candidate points; calculating first and second distances; and defining ellipsoid contour points. Calculating the ellipsoid parameter is based on the ellipsoid contour points and the center point. Calculating the adaptability ratio includes: drawing a complete ellipsoid; and calculating the adaptability ratio between the complete ellipsoid and the ellipsoid candidate. Eliminating the ellipsoid candidate is performed when the adaptability ratio is equal to or smaller than a threshold.

Abstract: A vital signal detecting apparatus is composed of sensors for detecting pulse waves, an A/D converter for converting analog signals, corresponding to the pulse waves and derived from the sensors, into digital signals, a separation matrix calculation means, and a signal separation calculation circuit. The separation matrix calculation circuit calculates a separation matrix for separating an outer disturbance caused by body movement from the pulse waves. The signal separation calculation means divides the digital signals converted by the A/D converter into a vital signal containing no outer disturbance and a body movement signal indicating the outer disturbance by using the separation matrix.

Abstract: A pulse wave sensor includes a detecting element and a sensor body. The pulse wave sensor is worn on the back side of a user's wrist corresponding to the back of the user's hand. The detecting element includes a translucent member on its top, and the translucent member has a convex surface. The detecting element is attached on the back side of the user's wrist by a dedicated belt so that the convex surface of the translucent member is in intimate contact with the surface of the user's skin. The sensor body is attached on the back side of the user's wrist by another dedicated belt so that it is arranged on the detecting element. A cushion is arranged between the sensor body and the detecting element. The pulse wave sensor can stably detect the pulse wave without being affected by the movement of the user's wrist.