A system and method for identifying a subject based upon ear recognition using a convolutional neural network (CNN) and handcrafted features, wherein an ear in an image is cropped using ground truth annotations and landmark detection is performed to obtain the information required to normalize pose and scale variations. The normalized images are then described by different feature extractors and matched through distance metrics. Finally, scores are fused and a subject identification decision is made.
Sarkar, Sudeep; Pamplona Segundo, Mauricio; and Hansley, Earnest Eugene, "Unconstrained ear recognition using a combination of deep learning and handcrafted features" (2019). USF Patents. 1027.
University of South Florida