By Yong Soo Kim, Young J. Ryoo, Moon-soo Jang, Young-Chul Bae
Intelligent platforms were initiated with the try to imitate the human mind. humans desire to allow machines practice clever works. Many strategies of clever platforms are in line with synthetic intelligence. in line with altering and novel necessities, the complicated clever platforms conceal a large spectrum: massive information processing, clever regulate, complex robotics, synthetic intelligence and computing device studying. This publication makes a speciality of coordinating clever structures with hugely built-in and foundationally practical elements. The e-book includes 19 contributions that includes social network-based recommender platforms, program of fuzzy enforcement, strength visualization, ultrasonic muscular thickness dimension, local research and predictive modeling, research of 3D polygon info, blood strain estimation approach, fuzzy human version, fuzzy ultrasonic imaging approach, ultrasonic cellular clever expertise, pseudo-normal photo synthesis, subspace classifier, cellular item monitoring, standing-up movement information approach, reputation constitution, multi-CAM and multi-viewer, powerful Gaussian Kernel, multi human move trajectory extraction and type coordination. This version is released in unique, peer reviewed contributions masking from preliminary layout to ultimate prototypes and authorization.
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Thus, the distance Dij between the i-th extracted position and the j-th past HMT is calculated as below. Dij = (P pi − μ j ) Σ−j 1 ( Ppi − μ j ) if det Σ j ≠ 0 T Ppi − Poj (15) Otherwise In (15), Ppi=(xpi, ypj) denotes a i-th extracted position, Poj =(xoj1 …xojM, yoj1 …yojM) denotes the j-th past HMT. μj, Σj denote the average matrix and the covariance matrix of Poj, respectively. figure 7 shows the concept of this step. In this figure, polygonal line with points represents HMT, black points represent new position, thick lines represent the distance and black thin lines shows normal distribution of the average matrix and corvariance matrix.
Finally, the estimated values are recorded as a comma-separated values (CSV) file and then visualized by a time-series graph. Gas meter image Gas meter Time Gas consumption(m3) 12:00 263293 12:01 263295 12:02 263296 12:03 263298 12:04 263299 Camera equipment Fig. 1. Outline of our system constitution CSV file Personal computer An Energy Visualization by Camera Monitoring 53 Numeral regions Counter region Frame Fig. 2. An example of gas meter image 3 Proposed Method Figure 3 shows a flowchart of the proposed method.
In the extracted HMTs images, Light color HMTs corresponding with figure 14 represent extracted HMTs and dark color HMTs represent ground truth of HMTs. Table 1. The average results of the experiment Data No. 0 Multi Human Movement Trajectory Extraction by Thermal Sensor 47 From Table 1 and figure 13, expect for the data #1, #3 and #9, the system obtained high GOOD. On the other hand, in the data #1, #3 and #9, OVER was high. In the all data, MISS was low. From these results, we confirm that the system successfully extracted HMTs.
Advanced Intelligent Systems by Yong Soo Kim, Young J. Ryoo, Moon-soo Jang, Young-Chul Bae