Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A similarity search may be performed on the image of a person, using visual characteristics and information that is known about the person. The search identifies images of other persons that are similar in appearance to the person in the image.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A similarity search may be performed on the image of a person, using visual characteristics and information that is known about the person. The search identifies images of other persons that are similar in appearance to the person in the image.

Abstract: 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.

Abstract: 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.

Abstract: The present invention meets these needs by providing temporal coherency to recognition systems. One embodiment of the present invention comprises a manifold recognition module to use a sequence of images for recognition. A manifold training module receives a plurality of training image sequences (e.g. from a video camera), each training image sequence including an individual in a plurality of poses, and establishes relationships between the images of a training image sequence. A probabilistic identity module receives a sequence of recognition images including a target individual for recognition, and identifies the target individual based on the relationship of training images corresponding to the recognition images. An occlusion module masks occluded portions of an individual's face to prevent distorted identifications.

Abstract: The present invention meets these needs by providing temporal coherency to recognition systems. One embodiment of the present invention comprises a manifold recognition module to use a sequence of images for recognition. A manifold training module receives a plurality of training image sequences (e.g. from a video camera), each training image sequence including an individual in a plurality of poses, and establishes relationships between the images of a training image sequence. A probabilistic identity module receives a sequence of recognition images including a target individual for recognition, and identifies the target individual based on the relationship of training images corresponding to the recognition images. An occlusion module masks occluded portions of an individual's face to prevent distorted identifications.

Abstract: 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.

Abstract: A similarity search may be performed on the image of a person, using visual characteristics and information that is known about the person. The search identifies images of other persons that are similar in appearance to the person in the image.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.