Blaine Rister

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Emerging mobile applications, such as augmented reality, demand robust feature detection at high frame rates. We present an implementation of the popular Scale-Invariant Feature Transform (SIFT) feature detection algorithm that incorporates the powerful graphics processing unit (GPU) in mobile devices. Where the usual GPU methods are inefficient on mobile(More)
Feature detection and extraction are essential in computer vision applications such as image matching and object recognition. The Scale-Invariant Feature Transform (SIFT) algorithm is one of the most robust approaches to detect and extract distinctive invariant features from images. However, high computational complexity makes it difficult to apply the SIFT(More)
Description of keypoints, or local image features, is widely employed in computer vision. However, the most successful techniques do not extend immediately to more than two spatial dimensions. In this paper, we describe robust methods for extracting local orientations and gradient histograms from higher-dimensional data, using these techniques to develop a(More)
We present a method for image registration based on 3D scale- and rotation-invariant keypoints. The method extends the scale invariant feature transform (SIFT) to arbitrary dimensions by making key modifications to orientation assignment and gradient histograms. Rotation invariance is proven mathematically. Additional modifications are made to extrema(More)
Content-based image retrieval is an emerging technology which could provide decision support to radiologists. This paper describes a system for content-based image retrieval based on 3D features extracted from liver lesions in abdominal computed tomography images. A supervised learning algorithm is developed to transform image features into search rankings.(More)
Exposed-datapath architectures yield small, low-power processors that trade instruction word length for aggressive compile-time scheduling and a high degree of instruction-level parallelism. In this paper, we present a general-purpose parallel accelerator consisting of a main processor and eight symmetric clusters, all in a single core. Use of a lightweight(More)
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