scholarly journals FPGA Implementation of Multi-scale Pedestrian Detection in Thermal Images

2016 ◽  
Vol 21 (3) ◽  
pp. 55-67
Author(s):  
Tomasz Kańka ◽  
Tomasz Kryjak ◽  
Marek Gorgon
Keyword(s):  
Vision System ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Thermal Images ◽  
Real Time Processing ◽  
Computing Platform ◽  
Multi Scale ◽  
Field Programmable ◽  
Window Approach ◽  
Silhouette Detection

Abstract In this paper an embedded vision system for human silhouette detection in thermal images is presented. As the computing platform a reprogrammable device (FPGA – Field Programmable Gate Array) is used. The detection algorithm is based on a sliding window approach, which content is compared with a probabilistic template. Moreover, detection is four scales in supported. On the used test database, the proposed method obtained 97% accuracy, with average one false detection per frame. Due to the used parallelization and pipelining real-time processing for 720 × 480 @ 50 fps and 1280 × 720 @ 50 fps video streams was achieved. The system has been practically verified in a test setup with a thermal camera.

scholarly journals Pedestrian detection algorithm based on improved muti-scale feature fusion

2021 ◽  
Vol 2078 (1) ◽  
pp. 012008
Author(s):  
Hui Liu ◽  
Keyang Cheng
Keyword(s):  
Clustering Algorithm ◽  
Feature Fusion ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Data Sets ◽  
False Detection ◽  
Scale Feature ◽  
Multi Scale ◽  
Dilated Convolution ◽  
Small Targets

Abstract Aiming at the problem of false detection and missed detection of small targets and occluded targets in the process of pedestrian detection, a pedestrian detection algorithm based on improved multi-scale feature fusion is proposed. First, for the YOLOv4 multi-scale feature fusion module PANet, which does not consider the interaction relationship between scales, PANet is improved to reduce the semantic gap between scales, and the attention mechanism is introduced to learn the importance of different layers to strengthen feature fusion; then, dilated convolution is introduced. Dilated convolution reduces the problem of information loss during the downsampling process; finally, the K-means clustering algorithm is used to redesign the anchor box and modify the loss function to detect a single category. The experimental results show that the improved pedestrian detection algorithm in the INRIA and WiderPerson data sets under different congestion conditions, the AP reaches 96.83% and 59.67%, respectively. Compared with the pedestrian detection results of the YOLOv4 model, the algorithm improves by 2.41% and 1.03%, respectively. The problem of false detection and missed detection of small targets and occlusion has been significantly improved.

scholarly journals FPGA Implementation of Multi-scale Face Detection Using HOG Features and SVM Classifier

2016 ◽  
Vol 21 (3) ◽  
pp. 27-44 ◽  
Author(s):  
Michał Drożdż ◽  
Tomasz Kryjak
Keyword(s):  
Face Detection ◽  
Vision System ◽  
Video Stream ◽  
Svm Classifier ◽  
Vast Number ◽  
Real Time Processing ◽  
Multi Scale ◽  
Svm Algorithm ◽  
Detection Window ◽  
Embedded Vision System

Abstract In this paper an FPGA based embedded vision system for face detection is presented. The sliding detection window, HOG+SVM algorithm and multi-scale image processing were used and extensively described. The applied computation parallelizations allowed to obtain real-time processing of a 1280 × 720 @ 50Hz video stream. The presented module has been verified on the Zybo development board with Zynq SoC device from Xilinx. It can be used in a vast number of vision systems, including diver fatigue monitoring.

Fast and Robust Pedestrian Detection Algorithm with Multi-Scale Orientation Features

2011 ◽  
Vol 22 (12) ◽  
pp. 3004-3014 ◽  
Author(s):  
Qi-Xiang YE ◽  
Jian-Bin JIAO ◽  
Shu-Qiang JIANG
Keyword(s):  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Multi Scale

Multi-scale vehicle and pedestrian detection algorithm based on attention mechanism

2021 ◽  
Vol 29 (6) ◽  
pp. 1448-1458
Author(s):  
Jing-yu LI ◽  
◽  
Jing YANG ◽  
Bin KONG ◽  
Can WANG ◽  
...  
Keyword(s):  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Attention Mechanism ◽  
Multi Scale
Sign in / Sign up

Export Citation Format

Share Document