RESUMO
Applications such as autonomous navigation, robot vision, and autonomous flying require depth map information of a scene. Depth can be estimated by using a single moving camera (depth from motion). However, the traditional depth from motion algorithms have low processing speeds and high hardware requirements that limit the embedded capabilities. In this work, we propose a hardware architecture for depth from motion that consists of a flow/depth transformation and a new optical flow algorithm. Our optical flow formulation consists in an extension of the stereo matching problem. A pixel-parallel/window-parallel approach where a correlation function based on the sum of absolute difference (SAD) computes the optical flow is proposed. Further, in order to improve the SAD, the curl of the intensity gradient as a preprocessing step is proposed. Experimental results demonstrated that it is possible to reach higher accuracy (90% of accuracy) compared with previous Field Programmable Gate Array (FPGA)-based optical flow algorithms. For the depth estimation, our algorithm delivers dense maps with motion and depth information on all image pixels, with a processing speed up to 128 times faster than that of previous work, making it possible to achieve high performance in the context of embedded applications.
RESUMO
There are a growing number of small children-as well as adults-with mental disabilities (including elderly citizens with Alzheimer's disease or other forms of age-related dementia) that are getting lost in rural and urban areas for various reasons. Establishing their location within the first 72 h is crucial because lost people are exposed to all kinds of adverse conditions and in the case of the elderly, this is further aggravated if prescribed medication is needed. Herein we describe a non-invasive, low-cost electronic device that operates constantly, keeping track of time, the geographical location and the identification of the subject using it. The prototype was made using commercial low-cost electronic components. This electronic device shows high connectivity in open and closed areas and identifies the geographical location of a lost subject. We freely provide the software and technical diagrams of the prototypes.
RESUMO
In Digital Holography there are applications where computing a few samples of a wavefield is sufficient to retrieve an image of the region of interest. In such cases, the sampling rate achieved by the direct and the spectral methods of the discrete Fresnel transform could be excessive. A few algorithmic methods have been proposed to numerically compute samples of propagated wavefields while allowing down-sampling control. Nevertheless, all of them require the computation of at least two 2D discrete Fourier transforms which increases the computational load. Here, we propose the use of an aliasing operator and a single discrete Fourier transform to achieve an efficient method to down-sample the wavefields obtained by the Fresnel transform.