scholarly journals Building an advanced invariant real-time human tracking system

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.

An Efficient Speckle Tracking Algorithm for Ultrasonic Imaging

2002 ◽  
Vol 24 (4) ◽  
pp. 215-228 ◽  
Author(s):  
Pai-Chi Li ◽  
Wei-Ning Lee
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Speckle Tracking ◽  
Search Strategy ◽  
Ultrasonic Imaging ◽  
Tracking Algorithm ◽  
Absolute Difference ◽  
Matching Process ◽  
Computation Efficiency ◽  
Clinical Breast

An efficient speckle tracking algorithm is proposed for motion estimation in ultrasonic imaging. Speckle tracking involves a matching process and a searching process. The matching process of the proposed algorithm is based on a Block Sum Pyramid algorithm that significantly reduces the computational complexity while maintaining the same accuracy as the conventional sum of absolute difference approach. The searching process, on the other hand, is based on a multilevel search strategy rather than the full-search strategy used by most conventional tracking methods. Both simulated speckle images and clinical breast images were used to test the performance of the proposed algorithm. The results show that the computation efficiency is improved by up to a factor of five over the conventional approach. The improved efficiency enables real-time or near-real-time implementation of motion estimation in ultrasonic imaging, which is particularly beneficial in areas such as blood flow estimation, elasticity imaging, speckle image registration, and strain compounding.

scholarly journals Study on the Moving Target Tracking Based on Vision DSP

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6494
Author(s):  
Xuan Gong ◽  
Zichun Le ◽  
Hui Wang ◽  
Yukun Wu
Keyword(s):  
Real Time ◽  
Visual Tracking ◽  
Tracking System ◽  
Direct Memory Access ◽  
Optimization Techniques ◽  
Tracking Algorithm ◽  
Scale Transformation ◽  
Time Performance ◽  
System Resources ◽  
The Impact

The embedded visual tracking system has higher requirements for real-time performance and system resources, and this is a challenge for visual tracking systems with available hardware resources. The major focus of this study is evaluating the results of hardware optimization methods. These optimization techniques provide efficient utilization based on limited hardware resources. This paper also uses a pragmatic approach to investigate the real-time performance effect by implementing and optimizing a kernel correlation filter (KCF) tracking algorithm based on a vision digital signal processor (vision DSP). We examine and analyze the impact factors of the tracking system, which include DP (data parallelism), IP (instruction parallelism), and the characteristics of parallel processing of the DSP core and iDMA (integrated direct memory access). Moreover, we utilize a time-sharing strategy to increase the system runtime speed. These research results are also applicable to other machine vision algorithms. In addition, we introduced a scale filter to overcome the disadvantages of KCF for scale transformation. The experimental results demonstrate that the use of system resources and real-time tracking speed also satisfies the expected requirements, and the tracking algorithm with a scale filter can realize almost the same accuracy as the DSST (discriminative scale space tracking) algorithm under a vision DSP environment.

Integration of Projection Histograms and Linear Prediction for Object Tracking

2012 ◽  
Author(s):  
Phaik Yong Yeoh ◽  
Syed Abdul Rahman Abu Bakar
Keyword(s):  
Motion Tracking ◽  
Linear Prediction ◽  
Tracking System ◽  
Prediction Method ◽  
Image Sequences ◽  
Moving Object ◽  
Tracking Algorithm ◽  
Potential Applicability ◽  
Experimental Image ◽  
Actual Location

Kertas kerja ini mengemukakan satu sistem visual untuk menjejak objek bergerak yang dapat beroperasi secara masa–nyata, efisien dan tahan lasak, dengan menggunakan turutan imej yang diperolehi daripada satu kamera statik. Algoritma menjejak yang dikemukakan menggabungkan teknik Unjuran Histogram dan kaedah Ramalan Linar untuk mencapai kelajuan menjejak yang lebih tinggi. Unjuran Histogram dilakukan untuk mendapatkan lokasi sebenar bagi objek yang dijejak, manakala kaedah Ramalan Linar disertakan dalam algoritma menjejak yang dikemukakan untuk meramal lokasi bagi objek bergerak dalam imej seterusnya, berdasarkan beberapa ukuran centroid sebelumnya. Hasil gabungan teknik Unjuran Histogram dan tertib kedua Ramalan Linar telah membolehkan algoritma yang dikemukakan untuk menjejak objek bergerak dengan tepat. Potensi and kecekapan bagi algoritma menjejak yang dikemukakan telah dibuktikan oleh keputusan menjejak yang baik pada beberapa turutan imej eksperimen. Kata kunci: menjejak pergerakan, Unjuran Histogram, Ramalan Linar, perbezaan bingkai In this paper, a real–time, efficient and robust visual tracking system for a single moving object using image sequences captured by a stationary camera is presented. The proposed tracking algorithm integrates the Projection Histograms technique with the Linear Prediction method in order to achieve a faster tracking speed. The Projection Histograms technique is applied to obtain the actual location of the tracked target, whereas the Linear Prediction method is incorporated in the proposed tracking algorithm to predict the location of the moving object in the next frame based on its several past centroid measurements. The Projection Histograms technique coupled with a second order Linear Prediction method has enabled the proposed algorithm to accurately track a single moving object. The potential applicability and efficiency of the proposed tracking algorithm has been validated by good tracking results on several experimental image sequences. Key words: Motion tracking, projection histograms, linear prediction, frame differencing

Real-time human tracking system with multiple omnidirectional vision sensors

2004 ◽  
Vol 35 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Takushi Sogo ◽  
Hiroshi Ishiguro ◽  
Mohan M. Trivedi
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Human Tracking ◽  
Omnidirectional Vision ◽  
Vision Sensors

Using Cumulative Histogram Maps in an Adaptive Color-Based Particle Filter for Real-Time Object Tracking

2010 ◽  
Vol 121-122 ◽  
pp. 585-590 ◽  
Author(s):  
San Lung Zhao ◽  
Shen Zheng Wang ◽  
Hsi Jian Lee ◽  
Hung I Pai
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
Tracking System ◽  
Target Object ◽  
Color Histogram ◽  
Human Tracking ◽  
Speed Up ◽  
Non Gaussian ◽  
The Cost ◽  
Gaussian Estimation

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.

The Design of Embedded Detecting and Tracking System

2011 ◽  
Vol 204-210 ◽  
pp. 1960-1963
Author(s):  
Zhong Hai Li ◽  
Dan Liu ◽  
Jian Guo Cui ◽  
Shen Li
Keyword(s):  
Signal Processing ◽  
Embedded System ◽  
Target Tracking ◽  
Real Time ◽  
Computer Technology ◽  
Tracking System ◽  
Tracking Algorithm ◽  
Embedded Technology ◽  
Target Detecting

On the basis of analyzing the character of target detecting and tracking algorithm, referencing the successful application of embedded system in the fields of electronics，signal processing and computer technology, combining target detecting and tracking and embedded technology, an embedded target tracking system is proposed which based on s3c24lO on which running clipping Linux system, and a tracking example of flying target is given. The whole system reaches the target of small size and good real-time. It’s a useful attempt to realize the small and intelligent of target tracking system.

Implementation and Optimization of Tracking System on Dual-DSP

2011 ◽  
Vol 58-60 ◽  
pp. 2231-2236
Author(s):  
Qiang Wu ◽  
Shi Dong Li ◽  
Le Gong Sun ◽  
Yu Fei Zhou
Keyword(s):  
Real Time ◽  
High Performance ◽  
Tracking System ◽  
Tracking Algorithm ◽  
Input And Output ◽  
Dual Core ◽  
Strong Ability ◽  
Low Consumption

The paper provides a solution of tracking system on dual-DSP(ADSP-BF561, ADP-BF548), and gives the method of implementation and optimization. The system implements the complex tracking algorithm in real time on the high-performance dual-core ADSP -BF561. The multimedia processor ADSP-BF548，which has integrated a pixel composer and many interfaces internally, is used to control the entire operating of the system and complete the task of input and output flexibly. With the help of the code and decode chips ADV7181 and ADV7171, which have strong ability of adaption to varieties of video formats, the system has the features of easy- expansibility, strong adaption, stabilize, function, small size and low consumption.

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

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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