Mr. Pritts is a researcher at the Center for Machine Perception (CMP) and a PhD candidate at Czech Technical University. His current research is detecting and modeling repeated patterns in images. Prior to joining CMP, Mr. Pritts had an industry career in computer vision and scientific computing. Mr. Pritts was a Lead Engineer for BAE Systems, where he contributed to several US Department of Defense (DARPA) computer-vision research efforts; at NASA, he created gesture-recognition software for remotely controlling robotic arms of the International Space Station; and for Shell Global Solutions, he designed high-performance process-control algorithms.
He received his BSc in Mathematics at The University of North Texas and his MSc in Computer Science from Czech Technical University.
Topic: The Bag of Words Torn Open: Image Retrieval goes Deep
Short Description: This talk will introduce an automated tuning method of a convolutional neural network for image retrieval from a large collection of unordered images. State-of-the-art retrieval and Structure-from-Motion (SfM) methods are used to obtain 3D models, which are used to guide the selection of the training data for CNN fine-tuning. Hard-positive
and hard-negative examples are shown to enhance the final performance in particular object retrieval with compact codes. Remarkably, the proposed method is on par with existing 256D compact representations even by using 32D image vectors. A comprehensive review of state-of-the-art image-retrieval systems using compact codes built from a bag-of-words image representation will be reviewed to motivate the proposed work.