BASIS视觉特征描述子及其硬件实现.pdf

BASIS视觉特征描述子及其硬件实现.pdf

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BASIS视觉特征描述子及其硬件实现

756 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 23, NO. 5, MAY 2013 The Nature-Inspired BASIS Feature Descriptor for UAV Imagery and Its Hardware Implementation Spencer G. Fowers, Dah-Jye Lee, Senior Member, IEEE, Dan A. Ventura, and James K. Archibald, Senior Member, IEEE Abstract—This paper presents a feature descriptor well suited for limited-resource applications such as an unmanned aerial vehicle embedded systems, small microprocessors, and small low-power field programmable gate array (FPGA) fabric. The basis sparse-coding inspired similarity (BASIS) descriptor utilizes sparse coding to create dictionary images that model the regions in the human visual cortex. Due to the reduced amount of com- putation required for computing BASIS descriptors, reduced de- scriptor size, and the ability to create the descriptors without the use of a floating point, this approach is an excellent candidate for FPGA hardware implementation. The bit-level-accurate BASIS descriptor was tested on a dataset of real aerial images with the task of calculating a frame-to-frame homography and compared to software versions of scale-invariant feature transform (SIFT) and speeded-up robust features (SURF). Experimental results show that the BASIS descriptor outperforms SIFT and performs comparably to SURF on frame-to-frame aerial feature point matching. BASIS descriptors require less memory storage than other descriptors and can be computed entirely in hardware, allowing the descriptor to operate at real-time frame rates on a low-power embedded platform such as an FPGA. Index Terms—Computer vision, feature description, feature descriptor, feature detection, feature detector, sparse coding. I. Introduction COMPUTER vision applications for low-power, limited-resource, and embedded systems are becoming increas- ingly prevalent. We define limited-resource systems as systems that have restricted or reduced processing capabilities due to weight, size, or power constraints

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