Real time human tracking system for defense application

The study presents a human tracking system. To tracking a person, we adopt a particle filter as tracking kernel, since the method has proven successful for tracking in non-linear and non-Gaussian estimation. In a particle filter, a set of weighted particles represents the possible target sates. In this study, we measure the weight according to both the appearances of the target object and background scene to improve the discriminability between them. In our tracker, the appearances are modeled as color histogram, since it is scale and rotation invariant. However, the color histogram extraction for a large number of overlap regions is repeated redundantly and inefficiently. To speed up it, we reduce the cost for calculating overlapped regions by creating a cumulative histogram map for the processing image. The experimental results show that the tracker has the best precision improvement, and the tracking speed is 49.7 fps for 384 × 288 resolution, when we use 600 particles. The results show that the proposed method can be applied to a real-time human tracking system with high precision.

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Building an advanced invariant real-time human tracking system

Computer Science and Information Systems ◽

10.2298/csis0701057i ◽

2007 ◽

Vol 4 (1) ◽

pp. 57-75

Author(s):

Fayez Idris ◽

Zaher Abu ◽

Rashad Rasras ◽

Emary El

Keyword(s):

Real Time ◽

Pattern Matching ◽

Personal Computer ◽

Tracking System ◽

Image Sequences ◽

Tracking Algorithm ◽

Human Tracking ◽

Absolute Difference ◽

To Come

Real-time human tracking is very important in surveillance and robot applications. We note that the performance of any human tracking system depends on its accuracy and its ability to deal with various human sizes in a fast way. In this paper, we combined the presented works in [1, 2] to come with new human tracking algorithm that is robust to background and lighting changes and does not require special hardware components. In addition this system can handle various scales of human images. The proposed system uses sum of absolute difference (SAD) with thresholding as has been described in [2] and compares the output with the predefined person pattern using the technique which has been described in [1]. Using the combination between [1,2] approaches will enhance the performance and speed of the tracking system since pattern matching has been performed according to just one pattern. After matching stage, a specific file is created for each tracked person, this file includes image sequences for that person. The proposed system handles shadows removal, lighting changes, and background changes with infinite pattern scales using standard personal computer.

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Development of real-time indoor human tracking system using LoRa technology

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v12i1.pp845-852 ◽

2022 ◽

Vol 12 (1) ◽

pp. 845

Author(s):

Ida Syafiza Binti Md Isa ◽

Anis Hanani

Keyword(s):

Real Time ◽

Tracking System ◽

Low Cost ◽

Power Level ◽

Human Tracking ◽

High Coverage ◽

Industrial Growth ◽

Received Signal Strength Indicator ◽

Positioning Method ◽

Testbed Implementation

<p>Industrial growth has increased the number of jobs hence increase the number of employees. Therefore, it is impossible to track the location of all employees in the same building at the same time as they are placed in a different department. In this work, a real-time indoor human tracking system is developed to determine the location of employees in a real-time implementation. In this work, the long-range (LoRa) technology is used as the communication medium to establish the communication between the tracker and the gateway in the developed system due to its low power with high coverage range besides requires low cost for deployment. The received signal strength indicator (RSSI) based positioning method is used to measure the power level at the receiver which is the gateway to determine the location of the employees. Different scenarios have been considered to evaluate the performance of the developed system in terms of precision and reliability. This includes the size of the area, the number of obstacles in the considered area, and the height of the tracker and the gateway. A real-time testbed implementation has been conducted to evaluate the performance of the developed system and the results show that the system has high precision and are reliable for all considered scenarios.</p>

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