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For mobile image matching applications, a mobile device captures a query image, extracts descriptive features, and transmits these features wirelessly to a server. The server recognizes the query image by comparing the extracted features to its database and returns information associated with the recognition result. For slow links, query feature compression(More)
M OBILE phones have evolved into powerful image and video processing devices, equipped with high-resolution cameras, color displays, and hardware-accelerated graphics. They are increasingly also equipped with GPS, and connected to broadband wireless networks. All this enables a new class of applications which use the camera phone to initiate search queries(More)
We have built 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. We avoid network latency by implementing the algorithm on the phone and deliver excellent performance by adapting a state-of-the-art image retrieval algorithm based(More)
To perform fast image matching against large databases, a Vocabulary Tree (VT) uses an inverted index that maps from each tree node to database images which have visited that node. The inverted index can require gigabytes of memory, which significantly slows down the database server. In this paper, we design, develop, and compare techniques for inverted(More)
Establishing visual correspondences is an essential component of many computer vision problems, which is often done with local feature-descriptors. Transmission and storage of these descriptors are of critical importance in the context of mobile visual search applications. We propose a framework for computing low bit-rate feature descriptors with a 20×(More)
We investigate transform coding to efficiently store and transmit SIFT and SURF image descriptors. We show that image and feature matching algorithms are robust to significantly compressed features. We achieve near-perfect image matching and retrieval for both SIFT and SURF using ∼2 bits/dimension. When applied to SIFT and SURF, this provides a 16×(More)
Many mobile visual search (MVS) systems transmit query data from a mobile device to a remote server and search a database hosted on the server. In this paper, we present a new architecture for searching a large database directly on a mobile device, which can provide numerous benefits for network-independent, low-latency, and privacy-protected image(More)
Streaming mobile augmented reality applications require both real-time recognition and tracking of objects of interest in a video sequence. Typically, local features are calculated from the gradients of a canonical patch around a keypoint in individual video frames. In this paper, we propose a temporally coherent keypoint detector and design efficient(More)
We present a method that unifies tracking and video content recognition with applications to Mobile Augmented Reality (MAR). We introduce the Radial Gradient Transform (RGT) and an approximate RGT, yielding the Rotation-Invariant, Fast Feature (RIFF) de-scriptor. We demonstrate that RIFF is fast enough for real-time tracking, while robust enough for large(More)