Abstract: A method and implementation of enhancing a facial recognition process to increase the judgment confidence on identifying a person from a large image database of multiple persons. The method may include reconstructing a database of 2D images having only a small number of images with respect to each person into a database having multiple images, perhaps hundreds or thousands, of each person. The multiple images represent different camera angles or different lighting conditions. The method further includes adding an extra confidence percentage to matching images in the database when multiple images of a person are identified as matching.

Abstract: An architecture and method useful for fast one-to-many image matching and image indexing. A plurality of images in a database are digitized into a plurality of descriptors. The descriptors are separated into a plurality of index groups. Index values for the images in the database are then calculated for the various index groups. An index value, for example, could be calculated as the average of the descriptors in a particular group. A source groups of images having particular index values over a particular threshold value are identified. When matching a target image to images in the database, the index values are calculated for the target image and compared to the threshold value. Source groups of images having similar index values over the threshold are then identified for further matching to the target image.

Abstract: A distributed memory computing environment is structured with an invariant memory page pool. The environment includes a device, a memory, a hard disk, and an operating system running on the device. A device ID lookup table and a Memory Block ID Lookup Table are stored in memory. Copies of memory pages and their look up tables are stored on the hard disk. If the operating system is shut down, at subsequent system start-up, memory is divided according to the same divisions seen on the memory page copies saved in configuration files.

Abstract: A computing environment for a device having a processor, a device memory and an operating system. A first process running in the operating system has a memory and a memory cache. A second process running in the operating system has a second process memory accessible to the first process. A communication channel between the first process and second process makes the second process memory available for the first process memory to use. The device memory is sectioned into memory blocks, each having a starting address. A block ID identifies the memory block. Data is stored in various memory units of the memory block. An offset ID identifies the memory unit. A DMCE Virtual address contains the offset ID, the block Id and a device ID for identifying the memory unit. The DMCE virtual address of a memory unit used for the memory function is copied into the memory cache.

Abstract: A distributed memory computing environment is structured with an invariant memory page pool. The environment includes a device, a memory, a hard disk, and an operating system running on the device. A device ID lookup table and a Memory Block ID Lookup Table are stored in memory. Copies of memory pages and their look up tables are stored on the hard disk. If the operating system is shut down, at subsequent system start-up, memory is divided according to the same divisions seen on the memory page copies saved in configuration files.

Abstract: A distributed memory computing environment is structured with an invariant memory page pool. The environment includes a device, a memory, a hard disk, and an operating system running on the device. A device ID lookup table and a Memory Block ID Lookup Table are stored in memory. Copies of memory pages and their look up tables are stored on the hard disk. If the operating system is shut down, at subsequent system start-up, memory is divided according to the same divisions seen on the memory page copies saved in configuration files.

Abstract: A distributed memory computing environment is structured with an invariant memory page pool. The environment includes a device, a memory, a hard disk, and an operating system running on the device. A device ID lookup table and a Memory Block ID Lookup Table are stored in memory. Copies of memory pages and their look up tables are stored on the hard disk. If the operating system is shut down, at subsequent system start-up, memory is divided according to the same divisions seen on the memory page copies saved in configuration files.

Abstract: A computing environment for a device having a processor, a device memory and an operating system. A first process running in the operating system has a memory and a memory cache. A second process running in the operating system has a second process memory accessible to the first process. A communication channel between the first process and second process makes the second process memory available for the first process memory to use. The device memory is sectioned into memory blocks, each having a starting address. A block ID identifies the memory block. Data is stored in various memory units of the memory block. An offset ID identifies the memory unit. A DMCE Virtual address contains the offset ID, the block Id and a device ID for identifying the memory unit. The DMCE virtual address of a memory unit used for the memory function is copied into the memory cache.

Abstract: A method and implementation of enhancing a facial recognition process to increase the judgment confidence on identifying a person from a large image database of multiple persons. The method may include reconstructing a database of 2D images having only a small number of images with respect to each person into a database having multiple images, perhaps hundreds or thousands, of each person. The multiple images represent different camera angles or different lighting conditions. The method further includes adding an extra confidence percentage to matching images in the database when multiple images of a person are identified as matching.

Abstract: An architecture and method useful for fast one-to-many image matching and image indexing. A plurality of images in a database are digitized into a plurality of descriptors. The descriptors are separated into a plurality of index groups. Index values for the images in the database are then calculated for the various index groups. An index value, for example, could be calculated as the average of the descriptors in a particular group. A source groups of images having particular index values over a particular threshold value are identified. When matching a target image to images in the database, the index values are calculated for the target image and compared to the threshold value. Source groups of images having similar index values over the threshold are then identified for further matching to the target image.