Methods, systems, and computer program products for image processing and computer vision using invariant features and deep learning techniques

A computer program product embodied on a non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor, causes the processor to execute a set of acts, the set of acts comprising:

• receiving one or more images or a sequence of images pertaining to a gait cycle of a person;
• processing the one or more images or the sequence of images;
• training or re-training a convolutional neural network using at least the one or more images or the sequence of images that has been processed, based at least in part upon one or more invariant features from the one or more images or the sequence of images;
• and
• recognizing a gait feature of the person to determine an identity of the person using at least the convolutional neural network that has been trained.

A system, comprising:

• at least one processor;
• memory that stores therein a sequence of instructions which, when executed by the at least one processor, causes the at least one processor to execute a set of acts, the set of acts comprising:
• receiving one or more images or a sequence of images pertaining to a gait cycle of a person;
• processing the one or more images or the sequence of images;
• training or re-training a convolutional neural network using at least the one or more images or the sequence of images that has been processed, based at least in part upon one or more invariant features from the one or more images or the sequence of images;
• and
• recognizing a gait feature of the person to determine an identity of the person using at least the convolutional neural network that has been trained.