The Impact of the Detector on the Performances of a Multi Person Tracking System

2021 ◽  
Vol 15 ◽  
Author(s):  
Djalal Djarah ◽  
Abdallah Meraoumia ◽  
Mohamed Lakhdar Louazene
Keyword(s):  
System Performance ◽  
Detection System ◽  
Tracking System ◽  
Pedestrian Detection ◽  
Dynamic Environment ◽  
Human Gait ◽  
Detection And Tracking ◽  
Tracking By Detection ◽  
Multi Person Tracking ◽  
The Impact

Background: Pedestrian detection and tracking is an important area of study in real-world applications such as mobile robots, human-computer interaction, video surveillance, pedestrian protection systems, etc. As a result, it has attracted the interest of the scientific community. Objective: Certainly, tracking people is critical for numerous utility areas which cover unusual situations detection, like vicinity evaluation and sometimes change direction in human gait and partial occlusions. Researchers primary focus is to develop surveillance system that can work in a dynamic environment, but there are major issues and challenges involved in designing such systems. So, it has become a major issue and challenge to design a tracking system that can be more suitable for such situations. To this end, this paper presents a comparative evaluation of the tracking-by-detection system along with the publicly available pedestrian benchmark databases. Method: Unlike recent works where the person detection and tracking are usually treated separately, our work explores the joint use of the popular Simple Online and Real-time Tracking (SORT) method and the relevant visual detectors. Consequently, the choice of the detector is an important factor in the evaluation of the system performance. Results: Experimental results demonstrate that the performance of the tracking-by-detection system is closely related to the optimal selection of the detector and should be required prior to a rigorous evaluation. Conclusion: The study demonstrates how sensitive the system performance as a whole is to the challenging of the dataset. Furthermore, the efficiency of the detector and the detector-tracker combination are also depending on the dataset.

scholarly journals Integer arithmetic approximation of the hog algorithm used for pedestrian detection

2017 ◽  
Vol 14 (2) ◽  
pp. 329-346 ◽  
Author(s):  
Srdjan Sladojevic ◽  
Andras Anderla ◽  
Dubravko Culibrk ◽  
Darko Stefanovic ◽  
Bojan Lalic
Keyword(s):  
Classification Accuracy ◽  
System Performance ◽  
Detection System ◽  
Pedestrian Detection ◽  
Lessons Learned ◽  
People Detection ◽  
Algorithm Performance ◽  
Integer Arithmetic ◽  
Point Arithmetic ◽  
Angle Calculation

This paper presents the results of a study of the effects of integer (fixed-point) arithmetic implementation on classification accuracy of a popular open-source people detection system based on Histogram of Oriented Gradients. It is investigated how the system performance deviates from the reference algorithm performance as integer arithmetic is introduced with different bit-width in several critical parts of the system. In performed experiments, the effects of different bit-width integer arithmetic implementation for four key operations were separately considered: HoG descriptor magnitude calculation, HoG descriptor angle calculation, normalization and SVM classification. It is found that a 13-bit representation of variables is more than sufficient to accurately implement this system in integer arithmetic. The experiments in the paper are conducted for pedestrian detection and the methodology and the lessons learned from this study allow generalization of conclusions to a broader class of applications.

scholarly journals Comparison of FairMOT-VGG16 and MCMOT Implementation for Multi-Object Tracking and Gender Detection on Mall CCTV

2021 ◽  
Vol 14 (1) ◽  
pp. 49-64
Author(s):  
Pray Somaldo ◽  
Dina Chahyati
Keyword(s):  
Detection System ◽  
Tracking System ◽  
Shopping Center ◽  
Specific Information ◽  
Gender Classification ◽  
Person Detection ◽  
Men And Women ◽  
Multi Person Tracking ◽  
And Gender ◽  
Gender Detection

The crowd detection system on CCTV has proven to be useful for retail and shopping sector owners in mall areas. The data can be used as a guide by shopping center owners to find out the number of visitors who enter at a certain time. However, such information was still insufficient. The need for richer data has led to the development of more specific person detection which involves gender. Gender detection can provide specific information on the number of men and women visiting a particular location. However, gender detection alone does not provide an identity label for every detection that occurs, so it needs to be combined with a multi-person tracking system. This study compares two tracking methods with gender detection, namely FairMOT with gender classification and MCMOT. The first method produces MOTA, MOTP, IDS, and FPS of 78.56, 79.57, 19, and 24.4, while the second method produces 69.84, 81.94, 147, and 30.5. In addition, evaluation of gender was also carried out where the first method resulted in a gender accuracy of 65\% while the second method was 62.35\%. 

scholarly journals Network Safety Policy Research for Analyzing Static and Dynamic Traffic Volume on the Basis of Data Mining

2014 ◽  
Vol 8 (1) ◽  
pp. 787-795
Author(s):  
Jing Xu
Keyword(s):  
Intrusion Detection ◽  
System Performance ◽  
Intrusion Detection System ◽  
Detection System ◽  
Policy Research ◽  
Single Layer ◽  
Integrated Network ◽  
Service Attack ◽  
Network Safety ◽  
The Impact

With popularization of network, higher requirement is proposed to intrusion detection system IDS for network safety consideration. The traditional electronic data processing is combined with safety auditing, which has become a necessary part of constituting integrated network safety technology at present, thus the methods as optimal matching mode and statistics, etc of intrusion detection system shall be adopted. This project shall respectively make comprehensive description to current situations of intrusion detection research via the aspects of intrusion detection research method (anomaly detection, misuse detection), intrusion detection system monitoring object (network based, host based), to comprehensively analyze the impact of intrusion detection system to system architecture. On this basis a network-based anomaly intrusion detection system NAIDS is designed to network anomaly intrusion, the association rules mining and frequent scenario mining are adopted to scan the intrusion characteristic, through static mining mode and dynamic mining mode, safety detection is conducted at single layer and domain layer, new type attack can be detected via improved NAIDS system. Next, NAIDS system performance shall be evaluated by aiming at various intrusion data. Generally speaking, the system performance can detect the rejection service attack and detection attack.

scholarly journals SIMULTANEOUS DETECTION AND TRACKING OF PEDESTRIAN FROM PANORAMIC LASER SCANNING DATA

2016 ◽  
Vol III-3 ◽  
pp. 295-302 ◽  
Author(s):  
Wen Xiao ◽  
Bruno Vallet ◽  
Konrad Schindler ◽  
Nicolas Paparoditis
Keyword(s):  
Energy Function ◽  
Laser Scanning ◽  
Moving Objects ◽  
Pedestrian Detection ◽  
Simultaneous Detection ◽  
Dynamic Environment ◽  
Space Time ◽  
Detection And Tracking ◽  
Nearest Point ◽  
Pedestrian Traffic

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, <i>Nearest-point</i> and <i>Max-distance</i>. Then, all the points on moving objects are transferred into a space-time (<i>x</i>, <i>y</i>, <i>t</i>) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.

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