Gabriel Takacs

TL;DR: An outdoors augmented reality system for mobile phones that matches camera-phone images against a large database of location-tagged images using a robust image retrieval algorithm and shows a smart-phone implementation that achieves a high image matching rate while operating in near real-time.

TL;DR: Mobile phones have evolved into powerful image and video processing devices equipped with high-resolution cameras, color displays, and hardware-accelerated graphics, which enables a new class of applications that use the camera phone to initiate search queries about objects in visual proximity to the user.

TL;DR: A framework for computing low bit-rate feature descriptors with a 20× reduction in bit rate is proposed and it is shown how to efficiently compute distances between descriptors in their compressed representation eliminating the need for decoding.

TL;DR: A framework for computing low bit-rate feature descriptors with a 20× reduction in bit rate compared to state-of-the-art descriptors is proposed and it is shown how to efficiently compute distances between descriptors in the compressed domain eliminating the need for decoding.

TL;DR: This work presents a method that unifies tracking and video content recognition with applications to Mobile Augmented Reality (MAR), and introduces the Radial Gradient Transform (RGT) and an approximate RGT, yielding the Rotation-Invariant, Fast Feature (RIFF) descriptor.