The authors propose an online image search engine based on local image keypoint matching with GPU support. State-of-the-art models are based on bag-of-visual-words, which is an analogy of textual search for visual search. In this work, thanks to the vector computation power of the GPU, the authors utilize real values of keypoint descriptors and realize real-time search at keypoint level. By keeping the identities of each keypoint, closest keypoints are accurately retrieved. Image search has different characteristics than textual search. The authors implement one-to-one keypoint matching, which is more natural for images. The authors utilize GPUs for every basic step. To demonstrate practicality of GPU-extended image search, the authors also present a simple bag-of-visual-words search technique with full-text search engines. The authors explain how to implement one-to-one keypoint matching with text search engine. Proposed methods lead to drastic performance and precision improvement, which is demonstrated on datasets of different sizes.
AND INTRODUCTIONWe present an energy harvesting technique that leverages readily available time-varying ambient electric field (EF) as source, and explore the utilization of surrounding everyday objects that are constructed from conductive materials. General concept of our approach is described in Figure 1, and the circuit model is depicted in Figure 2. We showed that by incorporating energy store and release circuitry, we were able to deliver power to a usable level. To thoroughly test the technique, we developed Wireless Logger hardware module and conduct extensive one week-long power harvesting experiment. The result is depicted in Figure 3. We show our ambient electric field profiler tool that checks the electrical properties of an environment. This tool is useful to obtain parameters to know whether our technique is feasible for a given environment. We highlight limitations that encourage us to refine our design, explore other grounding strategies, and implement techniques to extract the maximum harvestable energy in the future iterations of this strategy. We believe that the perpetual issue in Internet-of-Things is electrical power, and this research contributes as a simple, lightweight, thus usability-wise, a powerful solution for this issue.
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