Vast collections of documents available in image format need to be indexed for information
retrieval purposes. In this framework, word spotting is an alternative solution to optical …

Fast retrieval methods are critical for large-scale and data-driven vision applications. Recent
work has explored ways to embed high-dimensional features or complex distance functions …

Articulated hand-tracking systems have been widely used in virtual reality but are rarely
deployed in consumer applications due to their price and complexity. In this paper, we …

SIFT-like local feature descriptors are ubiquitously employed in computer vision applications
such as content-based retrieval, video analysis, copy detection, object recognition, photo …

Nearest-Neighbor Methods in Learning and Vision | Guide books skip to main content ACM
Digital Library home ACM Association for Computing Machinery corporate logo Google, Inc …

Defect reports are generated from various testing and development activities in software
engineering. Sometimes two reports are submitted that describe the same problem, leading …

Fast retrieval methods are critical for many large-scale and data-driven vision applications.
Recent work has explored ways to embed high-dimensional features or complex distance …

The task of similarity search is widely used in various areas of computing, including
multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of …

We present a new approach, called local discriminant embedding (LDE), to manifold
learning and pattern classification. In our framework, the neighbor and class relations of data …

The visual recognition problem is central to computer vision research. From robotics to
information retrieval, many desired applications demand the ability to identify and localize …