Tracking and Size Estimation of Objects in Motion using Optical flow and K-means Clustering

Gujunoori, Sagar; Oruganti, Madhu

doi:10.1109/icecit.2017.8456442

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…Many of them have the ultimate objective to reversely infer the exact user motion, and as such may involve complicated mathematical formulations and time-consuming optimization [27]. Other works looked at clustering the motion/optical flow vectors in the motion video to only identify distinct moving or stationary objects [28]. Our objective is similar to that of the latter.…”

Section: Related Workmentioning

confidence: 99%

Reducing VR Sickness by Directing User Gaze to Motion Singularity Point/Region as Effective Rest Frame

2023

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Simulation sickness is one major obstacle in proliferation of virtual reality. The sensory mismatch between the visual and vestibular senses about user motion is attributed as the main cause. One effective method has been the use of the rest frame, which refers to the reference object that remains fixed in position with respect to the user. A popular choice of the rest frame is the virtual nose, but it can direct one's attention away from the main part of the navigation content. We propose to instead use the area within the screen space that represents the least amount of motion in the navigation content, called the Motion Singularity Point/Region (MSP/R) as such a rest frame. Viewing such a region is thus expected to reduce the sensory conflict and ensuing sickness. Such a region can be found by analyzing the content with respect to motion and estimating the region(s) of the image space with the least relative amount of the total optical flow. We experimentally validated the VR sickness reduction effect of looking at the MSP/R compared to that of the virtual nose. In addition, we confirmed that the content agnostic MSP/R to be much coinciding with the user's natural viewing direction, making it less distracting from the main content. This makes the MSP/R a more practical and viable rest frame object for sickness reduction than e.g. the virtual nose.

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Section: Related Workmentioning

confidence: 99%

Reducing VR Sickness by Directing User Gaze to Motion Singularity Point/Region as Effective Rest Frame

2023

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“…We define the motion of the static background as rigid flow x rf A B δ → . Then, the projected 2D optical flow residuals x of A B δ → [30,31] on the image plane (see Figure 3) can be computed as:…”

Section: Optical Flow Residual Clusteringmentioning

confidence: 99%

A Visual SLAM Robust against Dynamic Objects Based on Hybrid Semantic-Geometry Information

Miao

Liu²,

Wei

et al. 2021

IJGI

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A visual localization approach for dynamic objects based on hybrid semantic-geometry information is presented. Due to the interference of moving objects in the real environment, the traditional simultaneous localization and mapping (SLAM) system can be corrupted. To address this problem, we propose a method for static/dynamic image segmentation that leverages semantic and geometric modules, including optical flow residual clustering, epipolar constraint checks, semantic segmentation, and outlier elimination. We integrated the proposed approach into the state-of-the-art ORB-SLAM2 and evaluated its performance on both public datasets and a quadcopter platform. Experimental results demonstrated that the root-mean-square error of the absolute trajectory error improved, on average, by 93.63% in highly dynamic benchmarks when compared with ORB-SLAM2. Thus, the proposed method can improve the performance of state-of-the-art SLAM systems in challenging scenarios.

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“…In this study, the optical flow method is used in the image segmentation process in separating moving objects (vehicles or other moving objects) from stationary objects (roads or other fixed objects) by producing a motion vector that will be thresholded to distinguish objects. This method has been used in various fields, such as facial expression recognition [4], disease detection [5], virtual reality [6], object recognition [7], people counting [8], and gesture recognition [9]. Many previous researchers have used the optical flow in the vehicle recognition field.…”

Section: Introductionmentioning

confidence: 99%

A Solution for Automatic Counting and Differentiate Motorcycles and Modified Motorcycles in Remote Area

Indrabayu¹,

Areni²,

Bustamin³

et al. 2022

IJACSA

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Motorcycles are the most significant contributor to the vehicle numbers in Indonesia, about 81% of all vehicles in the country. In addition, the growth of modified motorcycles has also increased in several areas, particularly remote places. Many studies have been conducted for detecting vehicles. However, most vehicle detection studies were conducted to detect cars or four-wheeled vehicles, and only a few studies were done to detect motorcycles. Further problems increase if the system is implemented in remote areas with limited electricity power resources that need low-cost budget specification computation. This study detects and calculates the number of motor vehicles and modified motorcycles passed on a highway from video data. It proposed Machine Learning instead of Deep Learning to suit the low computational video in remote areas. Computer visionbased methods used in the prediction are optical flow andHistogram Oriented Gradient (HOG) + Support Vector Machine (SVM). Five videos were used in the system testing, taken from the roadsides using a static camera with a resolution of 160x112 pixels at ±135º angle. This research showed that the accuracy of motorcycles and modified motorcycles detection and calculation systems using the HOG + SVM method is higher than the optical flow method. The average accuracy of HOG + SVM for motorcycles and modified motorcycles is 89.70% and 95.16%, respectively.

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Tracking and Size Estimation of Objects in Motion using Optical flow and K-means Clustering

Cited by 5 publications

References 9 publications

Reducing VR Sickness by Directing User Gaze to Motion Singularity Point/Region as Effective Rest Frame

Reducing VR Sickness by Directing User Gaze to Motion Singularity Point/Region as Effective Rest Frame

A Visual SLAM Robust against Dynamic Objects Based on Hybrid Semantic-Geometry Information

A Solution for Automatic Counting and Differentiate Motorcycles and Modified Motorcycles in Remote Area

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