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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Low-Cost Stereo Vision On An Fpga, Chris A. Murphy, Daniel Lindquist, Ann Marie Rynning, Thomas Cecil, Sarah Leavitt, Mark L. Chang Jul 2012

Low-Cost Stereo Vision On An Fpga, Chris A. Murphy, Daniel Lindquist, Ann Marie Rynning, Thomas Cecil, Sarah Leavitt, Mark L. Chang

Mark L. Chang

We present a low-cost stereo vision implementation suitable for use in autonomous vehicle applications and designed with agricultural applications in mind. This implementation utilizes the Census transform algorithm to calculate depth maps from a stereo pair of automotive-grade CMOS cameras. The final prototype utilizes commodity hardware, including a Xilinx Spartan-3 FPGA, to process 320times240 pixel images at greater than 150 frames per second and deliver them via a USB 2.0 interface.


Automated Least-Significant Bit Datapath Optimization For Fpgas, Mark L. Chang, Scott Hauck Jul 2012

Automated Least-Significant Bit Datapath Optimization For Fpgas, Mark L. Chang, Scott Hauck

Mark L. Chang

In this paper, we present a method for FPGA datapath precision optimization subject to user-defined area and error constraints. This work builds upon our previous research which presented a methodology for optimizing the dynamic range- the most significant bit position. In this work, we present an automated optimization technique for the least-significant bit position of circuit datapaths. We present results describing the effectiveness of our methods on typical signal and image processing kernels.


Interactionless Calendar-Based Training For 802.11 Localization, Mark Chang, Andrew J. Barry, Noah L. Tye Jul 2012

Interactionless Calendar-Based Training For 802.11 Localization, Mark Chang, Andrew J. Barry, Noah L. Tye

Mark L. Chang

This paper presents our work in solving one of the weakest links in 802.11-based indoor-localization: the training of ground-truth received signal strength data. While crowdsourcing this information has been demonstrated to be a viable alternative to the time consuming and accuracy-limited process of manual training, one of the chief drawbacks is the rate at which a system can be trained. We demonstrate an approach that utilizes users' calendar and appointment information to perform interactionless training of an 802.11-based indoor localization system. Our system automatically determines if a user attended a calendar event, resulting in accuracy comparable to our previously published …