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VLFeat is an open and portable library of computer vision algorithms. It aims at facilitating fast prototyping and reproducible research for computer vision scientists and students. It includes rigorous implementations of common building blocks such as feature detectors, feature extractors, (hierarchical) k-means clustering, randomized kd-tree matching, and(More)
We propose a method to identify and localize object classes in images. Instead of operating at the pixel level, we advocate the use of superpixels as the basic unit of a class segmentation or pixel localization scheme. To this end, we construct a classifier on the histogram of local features found in each superpixel. We regularize this classifier by(More)
Over the last decade, embedded sensing systems have been successfully deployed in a range of application areas, from education and science to military and industry. These systems are becoming more robust, capable, and widely adopted. Yet today, most sensor networks function in isolated patches, each with different mechanisms to deliver data to their users,(More)
oil organisms are the catalysts that link elemental exchange among the lithosphere, biosphere, and atmosphere. Understanding the rates of these exchanges, and the sequestration of elements within any pool, is becoming increasingly crucial to understanding soil processes and to sustainable management of local processes that are linked to the global climate.(More)
Inside the mammalian nose lies a labyrinth of bony plates covered in epithelium collectively known as turbinates. Respiratory turbinates lie anteriorly and aid in heat and water conservation, while more posterior olfactory turbinates function in olfaction. Previous observations on a few carnivorans revealed that aquatic species have relatively large,(More)
This paper presents the Golem Group/University of California at Los Angeles entry to the 2005 DARPA Grand Challenge competition. We describe the main design principles behind the development of Golem 2, the race vehicle. The subsystems devoted to obstacle detection, avoidance, and state estimation are discussed in more detail. An overview of vehicle(More)
This paper proposes a design for our entry into the 2006 AAAI Scavenger Hunt Competition and Robot Exhibition. We will be entering a scalable two agent system consisting of off-the-shelf laptop robots, capable of monocular vision. Each robot will demonstrate the ability to localize itself, recognize a set of objects, and communicate with peer robots to(More)
1.1 Bag of Features Pipeline. Here we show the bag of features pipeline. The color indicates the major area of each step. Blue boxes indicate data, which is partitioned into training and testing sets. The light orange boxes involve features, which are extracted from both sets. Yellow boxes correspond to steps involving the dictionary, including building the(More)