Abstract:
Affine-invariant extension of scale-invariant feature transform (ASIFT) algorithm requires a large amount of computation and memory access, and consequently, is hard to p...Show MoreMetadata
Abstract:
Affine-invariant extension of scale-invariant feature transform (ASIFT) algorithm requires a large amount of computation and memory access, and consequently, is hard to process in real time. In order to increase the operation speed of ASIFT algorithm, this paper proposes a new hardware architecture for the ASIFT algorithm. In order to reduce the memory access time, the affine transform is modified to allow external memory access in the raster-scan order with a little accuracy drop. In addition, image filtering with skewed kernel is proposed in order to reduce the memory space for image storage. Additional complexity reduction is attempted to reduce the number of simulated viewpoints. As a result, throughput of the affine transform module is increased to 325% and the proposed hardware processes a video graphics array-sized (640×480) video at 20 fps.
Published in: IEEE Transactions on Circuits and Systems for Video Technology ( Volume: 28, Issue: 11, November 2018)
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- IEEE Keywords
- Index Terms
- Scale-invariant Feature Transform ,
- Hardware Architecture ,
- Affine Transformation ,
- Amount Of Computation ,
- Operation Speed ,
- Memory Space ,
- External Memory ,
- Large Amount Of Computation ,
- Access In Order ,
- Solid Line ,
- Gaussian Filter ,
- Source Images ,
- Feature Matching ,
- Simulated Images ,
- Matching Score ,
- Matching Accuracy ,
- Image Rotation ,
- Camera Pose ,
- Imaging Buffer ,
- Correct Matches ,
- Image Memorability ,
- Nearest Neighbor Interpolation ,
- Pixel Line ,
- Order Memory ,
- System-on-chip ,
- Difference Of Gaussian ,
- Test Set Of Images ,
- Internal Memory ,
- Integer Lattice ,
- Scale Matrix
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Scale-invariant Feature Transform ,
- Hardware Architecture ,
- Affine Transformation ,
- Amount Of Computation ,
- Operation Speed ,
- Memory Space ,
- External Memory ,
- Large Amount Of Computation ,
- Access In Order ,
- Solid Line ,
- Gaussian Filter ,
- Source Images ,
- Feature Matching ,
- Simulated Images ,
- Matching Score ,
- Matching Accuracy ,
- Image Rotation ,
- Camera Pose ,
- Imaging Buffer ,
- Correct Matches ,
- Image Memorability ,
- Nearest Neighbor Interpolation ,
- Pixel Line ,
- Order Memory ,
- System-on-chip ,
- Difference Of Gaussian ,
- Test Set Of Images ,
- Internal Memory ,
- Integer Lattice ,
- Scale Matrix
- Author Keywords