scholarly journals An Efficient Real Time Object Tracking Based on HSV Value

2021 ◽  
Vol 9 (11) ◽  
pp. 1197-1203
Author(s):  
Sheikh Summerah
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
Moving Objects ◽  
Color Space ◽  
Video Tracking ◽  
Frame Rate ◽  
Long Distance ◽  
Hsv Color Space ◽  
Video Frames ◽  
Testing Stage

Abstract: This study presents a strategy to automate the process to recognize and track objects using color and motion. Video Tracking is the approach to detect a moving item using a camera across the long distance. The basic goal of video tracking is in successive video frames to link target objects. When objects move quicker in proportion to frame rate, the connection might be particularly difficult. This work develops a method to follow moving objects in real-time utilizing HSV color space values and OpenCV in distinct video frames.. We start by deriving the HSV value of an object to be tracked and then in the testing stage, track the object. It was seen that the objects were tracked with 90% accuracy. Keywords: HSV, OpenCV, Object tracking,

scholarly journals Object Tracking Using HSV Values and OpenCV

2021 ◽  
Vol 9 (12) ◽  
pp. 594-599
Author(s):  
Gowher Shafi
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
Moving Objects ◽  
Video Tracking ◽  
Frame Rate ◽  
Colour Space ◽  
Long Distance ◽  
Video Frames ◽  
Hsv Colour Space ◽  
Percent Accuracy

Abstract: This research shows how to use colour and movement to automate the process of recognising and tracking things. Video tracking is a technique for detecting a moving object over a long distance using a camera. The main purpose of video tracking is to connect target objects in subsequent video frames. The connection may be particularly troublesome when things move faster than the frame rate. Using HSV colour space values and OpenCV in different video frames, this study proposes a way to track moving objects in real-time. We begin by calculating the HSV value of an item to be monitored, and then we track the object throughout the testing step. The items were shown to be tracked with 90 percent accuracy. Keywords: HSV, OpenCV, Object tracking, Video frames, GUI

scholarly journals 3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4819
Author(s):  
Yikang Li ◽  
Zhenzhou Wang
Keyword(s):  
3D Reconstruction ◽  
Moving Objects ◽  
Structured Light ◽  
Color Space ◽  
Reconstruction Technique ◽  
Single Shot ◽  
Line Pattern ◽  
Hsv Color Space ◽  
Phase Map ◽  
Line Segmentation

Single-shot 3D reconstruction technique is very important for measuring moving and deforming objects. After many decades of study, a great number of interesting single-shot techniques have been proposed, yet the problem remains open. In this paper, a new approach is proposed to reconstruct deforming and moving objects with the structured light RGB line pattern. The structured light RGB line pattern is coded using parallel red, green, and blue lines with equal intervals to facilitate line segmentation and line indexing. A slope difference distribution (SDD)-based image segmentation method is proposed to segment the lines robustly in the HSV color space. A method of exclusion is proposed to index the red lines, the green lines, and the blue lines respectively and robustly. The indexed lines in different colors are fused to obtain a phase map for 3D depth calculation. The quantitative accuracies of measuring a calibration grid and a ball achieved by the proposed approach are 0.46 and 0.24 mm, respectively, which are significantly lower than those achieved by the compared state-of-the-art single-shot techniques.

The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space

2020 ◽  
Vol 97 ◽  
pp. 106805
Author(s):  
Ghazal Bargshady ◽  
Xujuan Zhou ◽  
Ravinesh C. Deo ◽  
Jeffrey Soar ◽  
Frank Whittaker ◽  
...  
Keyword(s):  
Pain Intensity ◽  
Facial Pain ◽  
Color Space ◽  
Hsv Color Space ◽  
Convolutional Networks ◽  
Video Frames

Video Tracking of Human with Occlusion Based on MeanShift and Kalman Filter

2013 ◽  
Vol 380-384 ◽  
pp. 3672-3677 ◽  
Author(s):  
Bao Hong Yuan ◽  
De Xiang Zhang ◽  
Kui Fu ◽  
Ling Jun Zhang
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Moving Objects ◽  
Video Tracking ◽  
Moving Object ◽  
Large Area ◽  
Image Region ◽  
Future State ◽  
Kalman Filter Algorithm ◽  
Histogram Similarity

In order to accomplish tracking of moving objects requirements, and overcome the defect of occlusion in the process of tracking moving object, this paper presents a method which uses a combination of MeanShift and Kalman filter algorithm. MeanShift object tracking algorithm uses a histogram to describe the color characteristics of an object, and search the location of an image region that the color histogram is closest to the histogram of the object. Histogram similarity is defined in terms of the Bhattacharya coefficient. When the moving object is a large area blocked, the future state of moving object is estimated by Kalman filter. Experimental results verify that the proposed algorithm achieves efficient tracking of moving objects under the confusing situations.

The Research of Motion Detection and Shadow Elimination in Video Surveillance

2012 ◽  
Vol 468-471 ◽  
pp. 2691-2694
Author(s):  
Zhi Li Qing ◽  
Yue Lin Chen
Keyword(s):  
Video Surveillance ◽  
Motion Detection ◽  
Moving Objects ◽  
Color Space ◽  
Video Image ◽  
Experimental Results ◽  
Background Model ◽  
Hsv Color Space ◽  
Shadow Elimination

This paper studies the moving objects detect and shadow eliminate in video surveillance. Completed the background generated on the video image by study the mixed Gaussian background model, by transforming the image to hsv color space for processing, which achieve the elimination of shadows. The experimental results show the approach this paper use is effectively on the background generated and shadow remove.

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