567 results about "Complexion" patented technology

The present invention is a method and system to provide a face-based automatic ethnicity recognition system that utilizes ethnicity-sensitive image features and probabilistic graphical models to represent ethnic classes. The ethnicity-sensitive image features are derived from groups of image features so that each grouping of the image features contributes to more accurate recognition of the ethnic class. The ethnicity-sensitive image features can be derived from image filters that are matched to different colors, sizes, and shapes of facial features—such as eyes, mouth, or complexion. The ethnicity-sensitive image features serve as observable quantities in the ethnic class-dependent probabilistic graphical models, where each probabilistic graphical model represents one ethnic class. A given input facial image is corrected for pose and lighting, and ethnicity-sensitive image features are extracted. The extracted image features are fed to the ethnicity-dependent probabilistic graphical models to determine the ethnic class of the input facial image.

The invention discloses an iris splitting method suitable for low-quality iris images. The prior art can not carry out robust splitting to the low-quality iris image with mass interference and noise. The invention uses a human eye detection algorithm to preliminarily determine a subimage of the human eye and is applied to image splitting based on interdependent histogram and cluster and ellipse Hough conversion to accurately determine the subimage of the human eye; improved Hough conversion is adopted to position the outer contour of the iris and output the integrodifferential operator value CID of a detection result; if the outer contour of the iris is not accurately positioned, parabola approximation is carried out on the image to judge whether the image is an eye-closed image; for the non eye-closed image, complexion information is utilized to re-determine the outer contour of the iris; the palpebra superior is detected by one-dimensional signal detection and parabola integrodifferential operator; the palpebra inferior is detected by one-dimensional signal detection and an RANSAC algorithm; the histogram in the iris is calculated; and a threshold value is found to remove a highly bright spot. The invention is used for iris splitting of low-quality iris image in a complex application context.

The invention discloses a method for tracking deformable hand gesture based on video streaming, comprising the steps of: obtaining a frame image, and extracting a sub-image containing a human hand from the obtained frame image; selecting feature tracking points from the sub-image containing the human hand, and initializing a continuously self-adaptive mean shift tracker by the sub-image containing the human hand; performing optical flow calculation on the selected feature tracking points to serve as a local tracking result, and synchronously overall tracking the human hand by the continuouslyself-adaptive mean shift tracker to obtain a global tracking result; updating the feature tracking points; and adopting the result of the optical flow tracking as the final output result of the deformable hand gesture. The method for tracking the deformable hand gesture based on video streaming can be used for tracking the human hand with randomly deformable hand gesture and enabling human-computer gesture interaction to operate in a more comfortable manner. According to the invention, the tracking can be performed aiming at the randomly deformable hand gesture, the interference from change of a background and a large area of complexion is eliminated, and the real-time robust hand gesture tracking is achieved.

The invention discloses a binocular vision-based human body posture and action research method. Firstly, internal and external parameters of a camera are acquired through binocular calibration, coordinates of a centroid point of each skin color area are extracted from an image shot by the camera, and the centroid point is matched and judged. Then, coordinates of the matched centroid point in a world coordinate system are found with the world coordinate system as a datum. Finally, the gesture and the action of the human body are judged according to the coordinates of the centroid point in the world coordinate system. According to the binocular vision-based human body posture and action research method, a large number of images do not need to be shot, centroid points of human body key parts such as the face and two hands can be matched in a three-dimensional mode through acquiring video frames in real time, the position relationship among the human body key parts is acquired, and the running cost is low.

An automatic detection method for normative wearing of a field personnel epidemic prevention mask comprises the steps that (1) a human face mask data set for normative wearing of the mask is collected, and the data set is marked and preprocessed; 2) a face mask target detection model is constructed, and the model is trained by adopting the marked face mask data set to obtain model parameters; 3) ato-be-detected video is inputted into the trained target detection model for positioning and classification, and whether to wear a mask or not is judged; and 4) whether to standardize the wearing ofthe mask or not is judged based on the YCrCb elliptical skin color model for the condition of judging the wearing of the mask. The invention further provides a corresponding detection device and a GPUcloud platform system. By adopting the method and the system, the detection precision and the detection speed of normative mask wearing of the human face can be effectively improved in complex scenessuch as target occlusion, dense crowds and small-scale detection, the detection method is simple, and engineering application landing conversion is easy.

The invention discloses a word vector model incremental study method. The super parameter used in the method comprises: a vector dimension, a number scope negative data, and a text window length; the word vector mode is updated dynamically to complete the vector model optimization and therefore complete the incremental study through initializing new words that appear in the additional text and sampling counterexample based on the historical glossary word-list; the technical scheme study can avoid to study repeatedly, historical data the calculating complexion degree is greatly reduced; the scheme can maintain the higher study efficiency so as to satisfy the efficiency requirement of the online system.

The invention discloses a vegetable fat composition cosmetic with a whitening effect and a preparation method of the cosmetic. The whitening vegetable fat with the whitening effect of the cosmetic is vegetable fat without any chemical synthetic grease, mineral oil, animal oil or the like; the contained vegetable fat includes citron fruit peel oil, erythropappa branch/leaf oil, camellia japonica seed oil, oxalis vidacea oil and the like. According to the test, the whitening vegetable fat composition cosmetic disclosed by the invention is nonirritant, safe and efficient. Moreover, the vegetable fat composition cosmetic has good effects of brightening skin and improving skin hyperpigmentation, has good compatibility with the skin, and has a refreshing sweet smell on the condition that no essences are added.

The invention relates to a method for picking up and identifying human ear characteristic by means of improved Hausdorff distance. The invention obtains standard human ear image through pretreatment of human ear image such as collection of human ear images, denoising of non-complexion noise, normalization of space dimension and illumination compensation; then, gray scale morphologic gradient and local threshold subdivision are adopted to pick up human ear edge feature so as to obtain standard human ear edge image. With the method and the Hausdorff distance improved through the length difference between standard variance and edge line segment, the influence of point set non-outline edge line segment point (outfield point) is reduced so as to obtain better anti-noise performance; moreover, the invention increases the accuracy of human ear edge image recognition by means of the characteristic value obtained on the basis of Hausdorff distance, thereby greatly increasing human ear recognition rate.

The invention provides a human hand detection method based on complexion. Acquired image to be detected is converted from an RGB color space to an HSV color space to acquire an HSV image. The image to be detected is converted from the RGB color space to an r-g color space to acquire an r-g image. The HSV image is converted into a first binary image. The r-g image is converted into a second binary image. Step-by-step operation is carried out on first and second binary images to acquire a comprehensive binary image. The comprehensive binary image is filtered to acquire an optimized binary image. The largest communication region in the optimized binary image is analyzed and is used as a skin region. A pre-trained K neighbor classifier is used to determine whether the largest communication region is hand-shaped to realize human hand recognition. The detection speed is fast. Human hand erroneous detection in gesture recognition is effectively solved.

The embodiment of the invention discloses a face detection method and device. The method comprises the following steps: carrying out edge detection processing on a preprocessed image obtained by preprocessing; obtaining an edge detection area and the length value, the width value and the length-width ratio of the edge detection area; according to the length value, the width value and the length-width ratio, obtaining a round area to be detected; carrying out expanded processing on the complexion area to the preprocessed image within the coverage range of the round area to be detected, and obtaining a first face contour; carrying out light compensation processing and complexion detection on the first light compensation image within the coverage range of the round area to be detected to obtain a second face contour; and combining a first face contour with a second face contour to obtain the face image. The device comprises a contour detection module, a complexion area expansion module, a light compensation and complexion detection module and a combination module. The embodiment of the invention avoids the phenomenon that face data is lost because of shadow caused by shading in the complexion detection process, and the accuracy rate and the detection speed of face detection can be improved.

A Chinese medicine complexion recognition method based on color modeling comprises the following steps: first collecting multiple pieces of human face images, then dividing each human face image into multiple skin blocks in a m*n size, forming a dataset by the skin blocks (all in four classes), dividing each dataset into a training sample set and a classic sample set, calculating the color feature vector of each skin block in the training sample set and the classic sample set, and respectively calculating the class center and the biggest radius of four classes of samples in each classic sample set; and through carrying out modeling on the modeling feature vectors nu of all classes of classic complexions, calculating the maximum value of the comprehensive deformation degree alpha of all classes of classic sample models and the maximum value of the similarity degree beta of the models, calculating the relative distance between each training sample and each class center in each classic sample set, calculating the class attribution factor lambda_s of each sample in each training sample set, calculating the fuzzy affiliation degree of each sample in each training sample set with the corresponding affiliated class, training a fuzzy support vector machine, and utilizing the well trained fuzzy support vector machine to carry out Chinese medicine complexion recognition.

The invention discloses a dynamic gesture recognition method based on complexion and morphological characteristics. The method includes: collecting video images to obtain a current video frame; performing complexion threshold value processing to the collected video frame to obtain a complexion binary image; subjecting the binary image to filtering and noise reduction to improve image quality; detecting and recognizing hand portion in the complexion binary image; recognizing motions of gesture according to gravity position information of the hand portion. The dynamic gesture recognition method based on complexion and morphological characteristics has the advantage of high instantaneity, short response time, capability to being applied to the field of human-computer interaction, low cost due to the fact that the method can be realized through a camera and a computer or processing equipment such as a DSP (digital signal processor), and high stability due to the fact that the method has better processing effect on rotation, translation and deformation of gestures.

The invention belongs to the design of a surface model of a medical simulation human organ and a preparation method, in particular to a preparation method for an infant cleft lip facial simulation model, which comprises the following steps: (1) collecting three-dimensional original data of faces of cleft lip illness children; (2) rebuilding digital facial models of the faces of the cleft lip illness children; (3) automatically layering and scattering model files and forming processing files; (4) automatically processing resin part models of the faces of the cleft lip illness children; (5) duplicating silastic cleft lip facial models; and (6) coloring the silastic facial models. The invention can provide a personalized customization facial simulation model which is in high consistence withthe shape, color, texture and the like of the faces of the cleft lip illness children with three age of months; the simulation model not only provides the real reference for a surgeon before operation, causes the surgeon to know fairly well during the operation, and simultaneously provides postoperative facial esthetic effects for parents of cleft lip and palate patients.

Systems and methods herein are developed which enable modification of an initial customized cosmetic product, wherein the initial customized cosmetic product is created based on an initial customized cosmetic product specification or an existing specification of a non-custom product. One such system and method for making a custom cosmetic product from an existing non-custom cosmetic product is configured to be capable of: characterizing a non-custom product with a known key comprised of at least one search component; providing user interaction to modify at least one of the at least one search components in this key to create a modified key; and using the modified key to produce custom product which may include determining manufacturing instructions. Such systems and methods may incorporate a custom or non-custom product attribute data base for providing product attribute data for modification and adjustment of the user search key using an adjustment service. Also incorporated herein are applications based on user interaction through two-dimensional complexion color maps derived using data associated with skin color, tone, morphology and/or biochemistry from a plurality of users.

The method of covering face of news interviewee via quick face detection includes the following steps: detecting the position and size of the news interviewee; verifying and compensating with complexion information; tracking the face of news interviewee with face complexion histogram; and extracting face contour and blurring processing by means of the facial position, region and complexion information. The automatic face detecting and covering technology can reach a face detecting rate up to 88 % in case of using no complexion information and cover almost the whole face while combining with the complexion information. Therefore, the present invention can reduce work strength and raise work efficiency.

The invention relates to an accurate positioning method for human eye on the basis of gray gradation information, belonging to the technical field of information. The method comprises: (1) human face detection: the area of a human face is positioned from an input image; (2) gray gradation column diagram analysis: gray gradation column diagram analysis is carried out on the human face image to determine the gray gradation range of the complexion area of the human face; (3) image strengthening: gray gradation adjustment is carried out on the image to enable eye characteristics to be more obvious; (4) Gabor wavelet filtration: Gabor wavelet filtration is carried out on the strengthened image, a real part image filtered by Gabor is synthesized to obtain a reference image; (5) cluster analysis: the synthesized reference image is analyzed by using the K-Means cluster method to obtain a binarization human eye candidate window, and the white area in each human eye candidate window after binarization is analyzed to determine the rough position of the human eye, so that the human eye window is obtained; (6) neighbourhood operation: the human eye window is scanned by two neighbourhood operators to determine the canter position of the pupilla. The invention has the advantages of simple detection method and accurate eye positioning.

The invention discloses a skin base solution and a preparation method thereof, belonging to the field of cosmetics. The skin base solution comprises deionized water, xanthan gum, 1,3-propanediol, 1,3-butanediol, sodium pyrrolidonecarboxylate, sodium hyaluronate, ethylene diamine tetraacetic acid, allantoin, methyl-p-hydroxybenzoate, polyoxyethylene (40) hydrogenated castor oil, phenylpropanol, apple stem cell essence, alpine rose stem cells, platinum matrix-EM, lipidure pmb, cactus stoste and rose damascus essential oil.. Active substance essences in the formulation can excite activity of a specific gene again, thereby promoting synthesis of repairing protein. After the skin base solution is used, people's skin becomes fine and smooth and is more uniform and is remarkably improved.

A traditional Chinese medicine face complexion diagnosing system belongs to the medical treatment health care equipment field. The present invention comprises a face image integration processor, an image collector, an image resolution device and a computer. The image collector respectively collects facial data and transmits the collected data to the face image integration processor. Fusions or overlaps of different images, which are formed after the treatment of the face image integration processor, are transmitted to the image resolution device. The image resolution device interprets and resets the data to obtain data and images of face complexions, which are input into the computer and compared with the database of the computer internal storage to generate identification results automatically. The present invention bases on the Internal Classic of Yellow Emperor, uses modern high technologies, solves the difficulties of human eyes in diagnosing the face complexions of traditional Chinese medicine and provides the traditional Chinese medicine face complexions diagnosing with the modern instrument and the quantitative index.

The invention discloses an anti-aging and wrinkle-removing composition. The anti-aging and wrinkle-removing composition is prepared from the following components in percentage by mass: 3-10% of hydrolyzed collagen, 3-15% of polypeptide, 0.4-10% of humectant, 1-3% of compound amino acid, 0.5-1% of ceramide-3, 3-10% of polyhydric alcohol, 1-10% of antioxidant, 0.1-1% of preservative, 0.02-1% of chelating agent, 0.1-5% of anti-allergic agent and the balance deionized water. According to the anti-aging and wrinkle-removing composition, the hydrolyzed collagen, the polypeptide, the humectant, the compound amino acid, the ceramide 3, the polyhydric alcohol and the antioxidant are scientifically proportioned according to the structural characteristics of skin and the physiological function requirements of the skin, so that the anti-aging and wrinkle-removing composition can be used for removing wrinkles instantly and removing wrinkles for a long time; and after the anti-aging and wrinkle-removing composition is used for a long time, the effects of reconstructing a skin cell collagen network, deeply removing wrinkles and resisting aging, plumping the skin, improving the water content of epidermal cells, enhancing the skin barrier function, brightening the skin, increasing the skin elasticity and brightening the skin color are achieved.

The invention relates to an assessment method of human body complexion, comprising the following steps: putting an image to be assessed in a first color space; carrying out the first assessment on the image to be assessed in the first color space; carrying out the second assessment on the result of the first assessment in the second space; determining the human body complexion area according to the result of the second assessment; extracting the color characteristics of the human body complexion area; and carrying out assessment on the human body complexion according to the color characteristics. The invention carries out assessment on the picture quality of a TV through the assessment of the human body complexion so as to realize the automatic detection of the human body complexion in the image or in the TV pictures.

An apparatus and method based on image for detecting heart rate activity is provided. The method includes: obtaining a plurality of color images; based on a complexion target condition, defining a target region; performing color composition analysis on the target region to obtain red channel signal, green channel signal and blue channel signal, respectively; performing independent component analysis on separate red, green and blue channel signals to obtain separate first independent component signal, second independent component signal and third independent component signal; performing frequency domain transform, signal energy computation and signal optimization processes on separate first, second and third independent component signals to obtain a filter signal, comparing filter signal based on a pre-set condition to determine if target region belonging to a human, and performing a physiological information analysis.

A TCM (Traditional Chinese Medicine) complexion automatic sorting method applying a superficial layer neural network belongs to the field of computer vision. The designed superficial layer neural network has five layers and adopts three different layer structures including an input layer, a characteristic extraction layer and an output layer. The input layer is composed of a convolution layer and a rectified linear unit (ReLU). The characteristic extraction layer is composed of three layers of network, wherein each of the first two layers is composed of a convolution layer and a ReLU activation function; one of the convolution layer and the ReLU is subjected to batch normalization and a pooling layer is added behind the second ReLU of the characteristic extraction layer; the third layer of the characteristic extraction layer is a whole connection layer connected with a ReLU in a followed manner. The output layer is composed of the whole connection layer and is provided with a followed softmax sorter. The method provided by the invention is distinctively advantaged in sorting precision and has invariance property in distortion such as zooming, translation, rotation and the like, is high in robustness and capable of improving sorting precision effectively. Therefore, the depth learning theory is applied to TCM face diagnose objectivity study.

The invention relates to a method for obtaining a human face outline, which comprises the following steps: carrying out threshold analysis on image data and establishing a complexion model in a YCbCrspace, initially positioning the complexion area through the complexion model, and marking a communicated area of the complexion area to further screen and remove a non-face area according to an areapixel; then extracting the initial outline of a human face and removing the neck outline by combining the face morphology proportion; and finally constructing the human face chin outline through humanface morphological constraining parameters and obtaining a continuous and closed human face outline. The method basically solves the problems that the chin outline is difficult to extract from the neck, can well extract the human face outline from images with relatively-complicated background, meet the requirements of characteristic extraction of the human outline, and has higher timeliness.