Adversarial Multi Scale Features Learning for Person Re Identification
Journal Title: International Journal of Trend in Scientific Research and Development - Year 2021, Vol 5, Issue 4
Abstract
Person re identification Re ID is the task of matching a target person across different cameras, which has drawn extensive attention in computer vision and has become an essential component in the video surveillance system. Pried can be considered as a problem of image retrieval. Existing person re identification methods depend mostly on single scale appearance information. In this work, to address issues, we demonstrate the benefits of a deep model with Multi scale Feature Representation Learning MFRL using Convolutional Neural Networks CNN and Random Batch Feature Mask RBFM is proposed for pre id in this study. The RBFM is enlightened by the drop block and Batch Drop Block BDB dropout based approaches. However, great challenges are being faced in the pre id task. First, in different scenarios, appearance of the same pedestrian changes dramatically by reason of the body misalignment frequently, various background clutters, large variations of camera views and occlusion. Second, in a public space, different pedestrians wear the same or similar clothes. Therefore, the distinctions between different pedestrian images are subtle. These make the topic of pre id a huge challenge. The proposed methods are only performed in the training phase and discarded in the testing phase, thus, enhancing the effectiveness of the model. Our model achieves the state of the art on the popular benchmark datasets including Market 1501, duke mtmc re id and CUHK03. Besides, we conduct a set of ablation experiments to verify the effectiveness of the proposed methods. Mrs. D. Radhika | D. Harini | N. Kirujha | Dr. M. Duraipandiyan | M. Kavya "Adversarial Multi-Scale Features Learning for Person Re-Identification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42562.pdf Paper URL: https://www.ijtsrd.comengineering/computer-engineering/42562/adversarial-multiscale-features-learning-for-person-reidentification/mrs-d-radhika
Authors and Affiliations
Mrs. D. Radhika | D. Harini | N. Kirujha | Dr. M. Duraipandiyan | M. Kavya
Keywords
Related Articles
- EP ID EP695826
- DOI -
- Views 78
- Downloads 0
Preparation and Standardization of Coconut, Dry Dates & Jaggery "Ladoo" and its Storage Study
The calcium and iron is common problem in children' lack of nutrients is one of the factors. Coconut dry dates & Jaggery was used for the development of ready-to-eat Indian traditional sweet meal commonly known as "ladoo...
Performance Analysis of Wireless Sensor Network in Smart Grid Environment
Wireless Sensor Networks WSNs is a strong candidate for smart grid applications, such as advanced metering infrastructure, demand response management, dynamic pricing, load control, electricity fraud detection, fault dia...
The Dilemma of Civilians Caught in an Armed Conflict
What becomes a full blown armed conflict usually begins with a small grievance which is most often neglected by those in position to solve them. The English adage which says “a stitch in time saves nine†is more ofte...
Dynamical Modelling and Control in the Polymer Extrusion Process
In this paper, the results of experimental investigation are using PVC molten is used as the coating material in a extrusion unit at different extruder temperatures, extruder speeds and shear rate value.The quality of ex...
Medico Legal Importance of Questioned Documents in Crime Investigation
Forensic handwriting examination has a new frontier the digital signature in biometric modality that uses, for recognition purposes, the anatomic and behavioral characteristics that an individual exhibit when signing her...