Abstract: A secondary curve, the ends of which coincide with the inner corner and the outer corner of the eye, is determined successively, and the total of the edge values of the pixels overlapping the secondary curve is calculated as an evaluation value. Next, a characteristic curve is generated on the basis of data made up of the calculated evaluation value and the Y-coordinate of the intersection between the secondary curve and a straight line passing through the center of a line segment whose ends coincide with the inner corner and the outer corner of the eye. Then, the reference positions for the upper eyelid and the lower eyelid of the eye are set on the basis of the result of an attempt to detect a pixel group occurring because of the red-eye effect in a search area defined on the basis of peaks in the characteristic curve.

Abstract: Distances between edges which are detected and paired from images which show a driver's face are computed sequentially. Based on a change in the computed distances, a low-probability candidate for a pair of eyelid edges is eliminated. The edge pairs ultimately remaining as a result thereof are detected as upper eyelid edge and lower eyelid edge pairings. It is thus possible to carry out a detection which takes into account not only a feature which is near to an eyelid edge, but also movement as an eyelid. Accordingly, it is possible to accurately detect edges of a driver's eyelids.

Abstract: A lower eyelid search window (W2) matching the pixels constituting the edge of a lower eyelid is transformed so that the lower eyelid search window (W2) fits the pixels constituting the edge of the lower eyelid. Then, the position of the centroid of the transformed lower eyelid search window (W2) is set as the lower eyelid reference position. Consequently, the lower eyelid reference position can be accurately set even if the lower eyelid search window (W2) is different in shape from the edge of the lower eyelid. Then, it is possible to accurately detect the degree of opening of the eyes of a driver and thus accurately determine the degree of wakefulness of the driver.

Abstract: An eye part detecting device has an image input section (21) for acquiring a face image, an eyelid edge labeling section (24) for detecting upper eyelid candidates and lower eyelid candidates which satisfy predetermined conditions for upper eyelids or lower eyelids in the face image, and an eyelid determination section (27) for comparing combinations of the upper and lower eyelid candidates to determine the combination of the upper and lower eyelid candidates whose relation best satisfies a predetermined condition as the upper and lower eyelids. The eyelid edge labeling section (24) classifies the horizontal edges and vertical edges calculated by an edge calculating section (23) into the upper eyelid candidates and the lower eyelid candidates according to a degree of how well the predetermined conditions are satisfied.

Abstract: An eyelid detection apparatus includes a face image storing means storing a plurality of face images of a subject captured at different timings, a change detecting means detecting changes in each face image caused by blinking after processing the plurality of face images stored by the face image storing means, and an eyelid detecting means detecting a position of an eyelid of the subject based on the changes detected by the change detecting means.

Abstract: Detecting with good precision an eye inside corner position and an eye outside corner position as face feature points even when the eye inside corner and/or the eye outside corner portions are obscured by noise. First eyelid profile modeling is performed with a Bezier curve expressed by a fixed control point P3 indicating an eye inside corner first position detected in an image, a fixed control point P4 indicating an eye outside corner first position, a control point P1 corresponding to an upper eyelid position candidate (first parameter), and a control point P2 corresponding to a lower eyelid position candidate (second parameter).

Abstract: An eyelid opening level determination device includes a face image taking unit; an upper eyelid detection unit for detecting an upper eyelid in the face image; a lower eyelid area setting unit for setting an area for searching a lower eyelid based on the upper eyelid; an edge group detecting unit for detecting an edge group where brightness changes from dark to bright as a lower eyelid candidate by scanning the area from an upper side to a lower side; a reliability value obtaining unit for obtaining a reliability value of the edge group; a lower eyelid determination unit in which the edge group having the reliability value exceeding a predetermined value in the edge group is determined to be the lower eyelid; and an eyelid opening level obtaining unit for obtaining opening level of the eyelid based on positions for the upper eyelid and the lower eyelid.

Abstract: A parking assisting device is equipped with a imaging device (1), a gaze position determining sections (3, 11), target parking position setting sections (1, 11), and a parking assisting section (2). The imaging device (1) takes images of surrounding of a vehicle. The gaze position determining sections (3, 11) determine positions at which a driver gazes. The target parking position setting sections (1, 11) sets target parking positions based on images taken by the imaging device (1) and gaze positions determined by the gaze position determining section (11). The parking assisting section (2) assists in processing to park the vehicle at the set target parking position.

Abstract: A computer (30) obtains a facial image acquired by picking up an image of a person subjected to image pickup from a camera (10), and estimates a facial expression of the person subjected to image pickup based on the obtained facial image. Next, the computer obtains an eye open level of the person subjected to image pickup based on the facial image, and sets a threshold of the eye open level based on the estimated facial expression of the person subjected to image pickup. When the eye open level exceeds the threshold, the computer (30) determines that the eye of the person subjected to image pickup is opened. Moreover, when the eye open level does not exceed the threshold, the computer determines that the eye of the person subjected to image pickup is closed.

Abstract: An image around a vehicle matching the intent of a driver is automatically displayed. An infrared camera (2) picks up an image of the face of a driver (7). A visual line direction and a face direction are detected from the face image of the driver (7). Based on the visual line direction of the driver (7) and the face direction thereof, a direction in which the driver (7) gazes is detected. When the direction in which the driver (7) gazes is included in image pickup ranges of CCD cameras (1A, 1B, and 1C), an image around a vehicle (100) picked up by any one of the CCD cameras (1A, 1B, and 1C) is automatically displayed on a monitor (6).

Abstract: Detecting with good precision an eye inside corner position and an eye outside corner position as face feature points even when the eye inside corner and/or the eye outside corner portions are obscured by noise. First eyelid profile modeling is performed with a Bezier curve expressed by a fixed control point P3 indicating an eye inside corner first position detected in an image, a fixed control point P4 indicating an eye outside corner first position, a control point P1 corresponding to an upper eyelid position candidate (first parameter), and a control point P2 corresponding to a lower eyelid position candidate (second parameter).

Abstract: A computer (30) obtains a facial image acquired by picking up an image of a person subjected to image pickup from a camera (10), and estimates a facial expression of the person subjected to image pickup based on the obtained facial image. Next, the computer obtains an eye open level of the person subjected to image pickup based on the facial image, and sets a threshold of the eye open level based on the estimated facial expression of the person subjected to image pickup. When the eye open level exceeds the threshold, the computer (30) determines that the eye of the person subjected to image pickup is opened. Moreover, when the eye open level does not exceed the threshold, the computer determines that the eye of the person subjected to image pickup is closed.

Abstract: An eyelid detection apparatus includes a face-image storing apparatus for storing an image of a face of a subject, an eyelid-candidate extracting apparatus for processing the image stored in the face-image storing apparatus to extract a pair of lines, which becomes a candidate of a combination of a line corresponding to an upper eyelid and a line corresponding to a lower eyelid, a parameter calculating apparatus for calculating a parameter, which indicates a possibility that a pan of the image stored in the face-image storing apparatus, the part corresponding to the pair of lines extracted by the eyelid-candidate extracting apparatus, includes at least one of outer and inner corners of an eye, and an eyelid detecting apparatus for detecting a position of an eyelid of the subject on the basis of the parameter calculated by the parameter calculating apparatus.

Abstract: An eye part detecting device has an image input section (21) for acquiring a face image, an eyelid edge labeling section (24) for detecting upper eyelid candidates and lower eyelid candidates which satisfy predetermined conditions for upper eyelids or lower eyelids in the face image, and an eyelid determination section (27) for comparing combinations of the upper and lower eyelid candidates to determine the combination of the upper and lower eyelid candidates whose relation best satisfies a predetermined condition as the upper and lower eyelids. The eyelid edge labeling section (24) classifies the horizontal edges and vertical edges calculated by an edge calculating section (23) into the upper eyelid candidates and the lower eyelid candidates according to a degree of how well the predetermined conditions are satisfied.

Abstract: An image around a vehicle matching the intent of a driver is automatically displayed. An infrared camera (2) picks up an image of the face of a driver (7). A visual line direction and a face direction are detected from the face image of the driver (7). Based on the visual line direction of the driver (7) and the face direction thereof, a direction in which the driver (7) gazes is detected. When the direction in which the driver (7) gazes is included in image pickup ranges of CCD cameras (1A, 1B, and 1C), an image around a vehicle (100) picked up by any one of the CCD cameras (1A, 1B, and 1C) is automatically displayed on a monitor (6).

Abstract: An eyelid opening level determination device includes a face image taking unit; an upper eyelid detection unit for detecting an upper eyelid in the face image; a lower eyelid area setting unit for setting an area for searching a lower eyelid based on the upper eyelid; an edge group detecting unit for detecting an edge group where brightness changes from dark to bright as a lower eyelid candidate by scanning the area from an upper side to a lower side; a reliability value obtaining unit for obtaining a reliability value of the edge group; a lower eyelid determination unit in which the edge group having the reliability value exceeding a predetermined value in the edge group is determined to be the lower eyelid; and an eyelid opening level obtaining unit for obtaining opening level of the eyelid based on positions for the upper eyelid and the lower eyelid.

Abstract: A device for detecting a road traveling lane, which is capable of stably defining a position of a boundary of a traveling lane. The device has edge point detection means (ED) for detecting a plurality of edge points in a contour on an image, edge histogram producing means (HD) for producing a vertical edge histogram for horizontal elements of the plurality of edge points, block marking line determination means (BD) for determining presence and absence of a block-like marking line on the basis of periodicity of distribution and a combination of distributions of plus edges and minus edges in the vertical edge histogram, and lane boundary edge detection means (MD) for detecting vertical edge points present outside (relative to the center of the traveling lane) of a region where the block-like marking line is present.

Abstract: A parking assisting device is equipped with a imaging device (1), a gaze position determining sections (3, 11), target parking position setting sections (1, 11), and a parking assisting section (2). The imaging device (1) takes images of surrounding of a vehicle. The gaze position determining sections (3, 11) determine positions at which a driver gazes. The target parking position setting sections (1, 11) sets target parking positions based on images taken by the imaging device (1) and gaze positions determined by the gaze position determining section (11). The parking assisting section (2) assists in processing to park the vehicle at the set target parking position.

Abstract: An eyelid detection apparatus includes a face-image storing apparatus for storing an image of a face of a subject, an eyelid-candidate extracting apparatus for processing the image stored in the face-image storing apparatus to extract a pair of lines, which becomes a candidate of a combination of a line corresponding to an upper eyelid and a line corresponding to a lower eyelid, a parameter calculating apparatus for calculating a parameter, which indicates a possibility that a pan of the image stored in The face-image storing apparatus, the part corresponding to the pair of lines extracted by the eyelid-candidate extracting apparatus, includes at least one of outer and inner corners of an eye, and an eyelid detecting apparatus for detecting a position of an eyelid of the subject on the basis of the parameter calculated by the parameter calculating apparatus.

Abstract: An eyelid detection apparatus includes a face image storing means storing a plurality of face images of a subject captured at different timings, a change detecting means detecting changes in each face image caused by blinking after processing the plurality of face images stored by the face image storing means, and an eyelid detecting means detecting a position of an eyelid of the subject based on the changes detected by the change detecting means.