摘要:
Systems for refinement of a segmentation of an image using spray-paint markup are disclosed, with methods and processes for making and using the same. Spray-paint markup allows for easy markup of errors in a segmentation. The markup's data may be correlated or harmonized with the representation of the segmentation, such that it may be applied to the segmentation. The markup's data is utilized to refine the segmentation errors. To assist in the refinement process, the resolutions may be scaled down so as to exert less computation burden during the process.
摘要:
The present invention relates to novel strains of lactic acid bacteria, Lactobacillus plantarum subsp. plantarum PM-A0087 deposited as NRRL accession number B-50523, Bifidobacterium longum PM-A0101 deposited as NRRL accession number B-50525, and Bifidobacterium bifidum PM-A0218 deposited as NRRL accession number B-50524.
摘要:
An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.
摘要:
An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.
摘要:
Systems for manifold learning for matting are disclosed, with methods and processes for making and using the same. The embodiments disclosed herein provide a closed form solution for solving the matting problem by a manifold learning technique, Local Linear Embedding. The transition from foreground to background is characterized by color and texture variations, which should be captured in the alpha map. This intuition implies that neighborhood relationship in the feature space should be preserved in the alpha map. By applying Local Linear Embedding using the disclosed embodiments, the local image variations can be preserved in the embedded manifold, which is the resulting alpha map. Without any strong assumption, such as color line model, the disclosed embodiments can be easily extended to incorporate other features beyond RGB color features, such as gradient and texture information.
摘要:
Systems for segmenting human hairs and faces in color images are disclosed, with methods and processes for making and using the same. The image may be cropped around the face area and roughly centered. Optionally, the illumination environment of the input image may be determined. If the image is taken under dark environment or the contrast between the face and hair regions and background is low, an extra image enhancement may be applied. Sub-processes for identifying the pose angle and chin contours may be performed. A preliminary mask for the face by using multiple cues, such as skin color, pose angle, face shape and contour information can be represented. An initial hair mask by using the abovementioned multiple cues plus texture and hair shape information may be created. The preliminary face and hair masks are globally refined using multiple techniques.
摘要:
An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.
摘要:
An input image is received, represented by a matrix D having a first number of dimensions. Each of the first number of dimensions may represent or correspond to a portion of the image. A metric objective may be identified. A dimensional reduction on the matrix D may then be performed that optimize the metric objective, so that a matrix d of a second number of dimensions is identified to represent the input image, where the second number of dimensions is less than the first number of dimensions.
摘要:
Systems for manifold learning for matting are disclosed, with methods and processes for making and using the same. The embodiments disclosed herein provide a closed form solution for solving the matting problem by a manifold learning technique, Local Linear Embedding. The transition from foreground to background is characterized by color and texture variations, which should be captured in the alpha map. This intuition implies that neighborhood relationship in the feature space should be preserved in the alpha map. By applying Local Linear Embedding using the disclosed embodiments, the local image variations can be preserved in the embedded manifold, which is the resulting alpha map. Without any strong assumption, such as color line model, the disclosed embodiments can be easily extended to incorporate other features beyond RGB color features, such as gradient and texture information.
摘要:
Embodiments described herein facilitate or enhance the implementation of image recognition processes which can perform recognition on images to identify objects and/or faces by class or by people.