2763 results about "Skin color" patented technology

A face feature analysis which begins by generating multiple face feature candidates, e.g., eyes and nose positions, using an isolated frame face analysis. Then, a nostril tracking window is defined around a nose candidate and tests are applied to the pixels therein based on percentages of skin color area pixels and nostril area pixels to determine whether the nose candidate represents an actual nose. Once actual nostrils are identified, size, separation and contiguity of the actual nostrils is determined by projecting the nostril pixels within the nostril tracking window. A mouth window is defined around the mouth region and mouth detail analysis is then applied to the pixels within the mouth window to identify inner mouth and teeth pixels and therefrom generate an inner mouth contour. The nostril position and inner mouth contour are used to generate a synthetic model head. A direct comparison is made between the inner mouth contour generated and that of a synthetic model head and the synthetic model head is adjusted accordingly. Vector quantization algorithms may be used to develop a codebook of face model parameters to improve processing efficiency. The face feature analysis is suitable regardless of noise, illumination variations, head tilt, scale variations and nostril shape.

A system and a method for rapidly tracking multiple faces uses a face-like region generator to find a face-like region by skin color, motion, and silhouette information. A face tracking engine tracks faces based on new and old faces, and skin colors provided by the face-like regions. The tracked face is fed into a face status checker for determining whether the face-like regions are old faces tracked in a previous frame or are possible new faces. If the face-like regions are old faces, a face verification engine checks whether there exists a predefined percentage of overlapping area between an old face and a skin region. If yes, the old face is still in the current frame and its position is in the center of the skin region, otherwise, the position of the old face is found by a correlation operation.

A face detection method based on a skin color and a pattern match. A face detection method includes: detecting skin color pixels using color information of an image; calculating a proportion of the skin color pixels occupying each predetermined sub-window of the image; selecting ones of the predetermined sub-windows as face candidates when the proportions of the skin color pixels in the ones of the sub-windows are at least equal to a threshold value; and determining whether any of the face candidates is a face and storing a location of the face.

A gesture recognition system using a skin-color based method combined with motion information to achieve real-time segmentation. A Kalman filter is used to track the centroid of the hand. The palm center, palm bottom, as well as the largest distance from the palm center to the contour from extracted hand mask are computed. The computed distance to a threshold is then compared to decide if the current posture is “open” or “closed.” In a preferred embodiment, the transition between the “open” and “closed” posture to decide if the current gesture is in “select” or “grab” state.

A system and method for acquiring, processing, and comparing an image with a stored image to determine if a match exists. In particular, the system refines the image data associated with an object based on pre-stored color values, such as flesh tone color. The system includes a storage element for storing flesh tone colors of a plurality of people, and a defining stage for localizing a region of interest in the image. A combination stage combines the unrefined region of interest with one or more pre-stored flesh tone colors to refine the region of interest based on color. This flesh tone color matching ensures that at least a portion of the image corresponding to the unrefined-region of interest having flesh tone color is incorporated into the refined region of interest. Hence, the system can localize the head, based on the flesh tone color of the skin of the face in a rapid manner. According to one practice, the refined region of interest is smaller than or about equal to the unrefined region of interest. This method and apparatus are particularly adapted to consumer devices such as hand-held devices and cars.

A method and device for treating biological external tissue using at least one energy source. The energy source can be incoherent light, coherent light, a radio frequency, ultrasound, a laser, or any other type of energy that can be applied through the device. The features of various embodiments of the device include the generation of positive pressure and/or negative pressure through one or more pressure conduits, the application of an object within a recess of the device, and measurements through various sensors on the device. These sensors can be monitored and/or controlled through a display element having rows and columns of pixels on the device. The device can be a handheld device or an add-on to existing devices in some embodiments, and can include skin color sensors, temperature sensors, and capacitance sensors.

An object detector, an object detecting method and a robot can reduce diction errors of detecting wrong objects without increasing the volume of the computational operation to be performed to detect the right object. A face detector 101 comprises a face detecting section 110 that operates like a conventional face detecting section and is adapted to roughly select face candidates from an input image by template matching and detect face candidates by means of a support vector machine for face recognition, a non-face judging section 120 that detects non-face candidates that are judged to be non-faces and removes them from the face candidates selected by the face detecting section 110 and a skin tracker section 114 for tracking a face region after the non-face judgment. When the assumed distance between the face detector and the face as computed from the input image and the measured distance as measured by a distance sensor show a large difference, when the color variance of the face candidate is small, when the occupancy ratio of the skin color region is large and when the change in the size of the face region is large after the elapse of a predetermined time, the non-face judging section 120 judges such face candidates as non-faces and removes them from the face candidates.

Improved methods and apparatuses are provided for use in face detection. The methods and apparatuses significantly reduce the number of candidate windows within a digital image that need to be processed using more complex and/or time consuming face detection algorithms. The improved methods and apparatuses include a skin color filter and an adaptive non-face skipping scheme.

A method and a device of light source discrimination, skin color correction, and color image correction, and storage medium thereof capable of being read by a computer always enable reproducibility, of color to be maintained highly regardless of difference of light source. There is calculated color distribution of portion of a face or skin in image by color distribution calculation section. There is compared the color distribution with distribution of skin color taken photograph under respective light sources stored in reference color distribution storage section. A light source discrimination section discriminates the light source at the time of taking photograph. There is corrected color by converting color under the light source of candidate substance into a corresponding color under standard light source.

A method for detecting objects in a digital image includes the steps of generating a first segmentation map of the digital image according to a non-object specific criterion, generating a second segmentation map of the digital image according to an object specific criterion, and detecting objects in the digital image using both the first and second segmentation maps. In a preferred embodiment of the invention, the non-object specific criterion is a color homogeneity criterion and the object specific criterion is an object specific color similarity, wherein the object specific color is skin color and the method further comprises the step of detecting red-eye in the detected skin color regions.

A digital camera (10) includes a face detecting section (74), a color temperature detecting section (76) and a flash device (86) having an LED array in which RGB LEDs are regularly arranged as a light source. When a shutter button (18) is pressed halfway, the face detecting section (74) reads out image data of a through image from a memory (60) and detects a person's face in the image. A CPU (64) identifies a scene based on brightness values of face and surrounding areas as, for example, a backlit scene, and specifies a face peripheral area according to an exposure pattern corresponding to the backlit scene. When the shutter button (18) is fully pressed, the CPU (64) sends a flash projection command to an LED control circuit (87), thereby illuminating the LEDs corresponding to the face peripheral area. By controlling illumination of the RGB LEDs, the LED control circuit (87) directs to project the flash light having color temperature that corrects the person's face color into an appropriate skin color.

The invention discloses a face detection and recognition method based on skin color segmentation and template matching. A face is segmented with the use of a face skin mixing Gauss model according to the clustering characteristics of face skin color in an YCbCr color space and a region of which the color is close to face skin color is separated from an image so as to achieve the purpose of quickly detecting the outer face of a face. A light compensation technology is used to overcome the influence of brightness on face detection and recognition. Adaptive template matching is used to overcome the influence of a skin-color-alike background on face detection and recognition. A secondary matching algorithm is adopted to reduce the amount of computation during the matching process, and singular value features of a face image are extracted to recognize a face and achieve the purpose of reducing the number of dimensions of a characteristic value matrix in the process of face feature extraction. The face detection and recognition method can quickly detect a face, improves the accuracy of face detection and recognition, is strong in practicability and has strong popularization and application values.

A method and a system for heart rate measurement are provided. The method includes: capturing at least one image, detecting skin-like points by using a skin color detector, labeling the skin-like points and tracking at least one target to be measured, taking statistics on color values of the target at multiple time points, measuring the heart rate through frequency transformation. The method and the system are easy to setup fully an automatic contact-free measurement of multiple persons' heart rates at a time, and applicable in multiple regions of human body for heart rate measurement such as head and neck, arm, and palm regions.

A stable composition is provided to treat and/or prevent photo-aged skin and related skin disorders such as sunburn, wrinkles, poor skin tone and skin discoloration by topically applying to the skin the treatment composition containing an effective amount of a compound such as ascorbic acid, derivatives of ascorbic acid and/or extracts containing ascorbic acid, in a pharmaceutically acceptable vehicle containing a substantially anhydrous base having no water added. The anhydrous base stabilizes the compound, so that the compound remains effective for an effective period of time, even in the presence of exposure to water.

The invention relates to a removing method for a glasses frame in a face image. The method comprises the steps of: detecting and positioning eyes in the input face image with a pair of glasses, geometrically correcting the face image on the basis of the positioned result to form a first image; extracting an eye estimation area from the first image to obtain a second image, and conducting mathematical morphology processing on the second image so as to determine the position of a glasses frame; based on the first image, establishing a face skin color model; in the second image, interpolating each pixel point of the glasses frame the position of which is determined, correcting the interpolation result in a part of pixel points of the glasses frame according to the skin color model, and conducting de-noising processing to form a ninth image; and replacing the eye estimation area in the first image by the ninth image, synthesizing and outputting the face image the glasses frame of which is removed. According to the technical scheme, the glasses frame in the face image with a pair of glasses can be conveniently and effectively removed, and the face recognition rate can be further improved.

A digital image processing method for locating human eyes in a digital image, includes the steps of detecting a skin colored region in the image; detecting human iris color pixels in the skin colored region; forming initial estimates of eye positions using the locations of the detected iris color pixels in the skin colored region; estimating the size of each eye based on the distance between the estimated initial eye positions; forming a first search window for one eye, the center of the window being the estimated initial position for the one eye and the size of the window being proportional to the estimated size of the one eye; and employing a template to locate an eye in the first search window.

The invention discloses a gesture identification method and a gesture identification system, wherein the method comprises the following steps: step S1, a gesture detecting step: detecting a gesture in video stream in real time, marking a region in which the gesture is detected as an interested region; step S2, a gesture segmenting step: processing the interested region by utilizing skin color segmentation, and then performing edge detecting and outline extracting to obtain a point sequence of a hand-shaped outline; step S3, a gesture identifying step: firstly extracting a Fourier descriptor of the hand-shaped outline and then mapping the Fourier descriptor to a new vector of a characteristic space by utilizing PCA (principal components analysis), comparing the distance between the new vector and a gesture clustering center obtained by training, and judging a gesture type represented by the vector. The gesture identification method and the gesture identification system disclosed by the invention can improve the gesture identification accuracy and the gesture identification efficiency, and can effectively avoid background color interference.

An original pupil color of a subject person in an image in which an abnormality such as a red-eye or gold-eye occurs is estimated. Further, whether an image correction is required or not and to produce an image having a natural pupil color in the image correction by estimating the original pupil color from the image is judged. A pupil color estimating device has a skin color of a subject person specified from an inputted image, regardless of whether an abnormality such as a red-eye or gold-eye occurs. This skin color is substituted in an approximate equation based upon a statistical result carried out in advance, and thereby a normal color component of a pupil is estimated from the skin color of the subject person.

Devices and methods having a cooling material and reduced pressures to treat biological external tissue using at least one energy source are disclosed. The cooling material may be water, ethyl alcohol, and/or any other material having a vapor pressure below atmospheric pressure. The energy source may be incoherent light, coherent light, a radio frequency, ultrasound, a laser, and/or any other type of energy that can be applied through the device. The features of various embodiments of the device include the generation of positive pressure and/or negative pressure through one or more pressure conduits, the application of an object within a recess of the device, and measurements through various sensors on the device. These sensors may be monitored and/or controlled through a display element having rows and columns of pixels on the device. The device may be a handheld device or an add-on to existing devices in some embodiments, and may include skin color sensors, temperature sensors, motion sensors, vapor pressure sensors, material sensors, and/or capacitance sensors.

The invention discloses a method for quickly and accurately detecting and tracking a human face based on a video sequence, which relates to the technical field of mode identification. The method comprises the following steps of: 1, extracting a video frame image from a video stream; 2, preprocessing the video frame image, namely compensating light rays, extracting skin color areas, performing morphological processing and combining the areas; 3, detecting the human face, namely representing the human face by using Harr-like characteristics and detecting the human face by using a cascaded Adaboost algorithm with an assistant decision function; 4, establishing the characteristics of the human face, namely detecting the area characteristics of the detected human face and the shape characteristics of the edge profile of the human face; 5, tracking the human face, particularly tracking the human face by using a human face area characteristic model when an intersection does not occur in a human face area, and further matching when the intersection occurs according to the shape characteristics of the edge profile of the human face; and 6, extracting the sequence of a human face image. By the technical method, the human face can be detected and tracked quickly and accurately on the basis of the video sequence.

A method and a system for gesture recognition are provided for recognizing a gesture performed by a user in front of an electronic product having a video camera. In the present method, an image containing the upper body of the user is captured and a hand area in the image is obtained. The hand area is fully scanned by a first couple of concentric circles. During the scanning, a proportion of a number of skin color pixels on an inner circumference of the first couple of concentric circles and a proportion of a number of skin color pixels on an outer circumference of the first couple of concentric circles are used to determine a number of fingertips in the hand area. The gesture is recognized by the number of fingertips and an operation function of the electronic product is executed according to an operating instruction corresponding to the recognized gesture.

In a video game, a player is allowed to create a character in the video game by selecting feature variables that define a character feature according to two or more target features and a feature variable. The target features can be are morph targets and the feature variable might represent relative distance of the player's desired feature relative to the morph targets. In a specific example, the player might be presented with two face shapes as morph targets and an input slider for a corresponding feature variable where the resulting face feature of the character matches one of the morph targets when the input slider is at one extreme, matches the other morph target when the input slider is at the other extreme and is a combination of the morph targets when the input slider is between the extremes. The character features might include face shape, height, weight, skin color, skin texture, body build, particular sports figures' faces, clothing, hair, eyes, nose, mouth, lips, hands, feet, etc. The player can also purchase items from a shop according to restrictions on cost, sponsorship, availability, time of day, date and/or day of year.