2D shape estimation for moving objects with a moving camera and cast shadows

1998 ◽  
Author(s):  
Roland Mech ◽  
Juergen Stauder
Keyword(s):  
Moving Objects ◽  
Shape Estimation ◽  
Moving Camera

DETECTION OF MOVING OBJECT USING REMAINED BACKGROUND UNDER MOVING CAMERA

2007 ◽  
Vol 04 (03) ◽  
pp. 227-236 ◽  
Author(s):  
TAEHO KIM ◽  
KANG-HYUN JO
Keyword(s):  
Correlation Coefficient ◽  
Moving Objects ◽  
Displacement Vector ◽  
Image Sequence ◽  
Moving Object ◽  
Pixel Intensity ◽  
Current Image ◽  
Moving Camera ◽  
Lower Weight ◽  
Displacement Vectors

A background is a part that does not vary too much or change frequently in an image sequence. Using this assumption, an algorithm of reconstructing remained background and detecting moving objects for static and also moving camera is presented. For generating background, we detect regions that have high correlation coefficient compared within prior pyramid images from the current image. These detected regions are used for two process. First, we calculate the temporal displacement vector of each detected regions and classify clusters of pixel intensity based on camera movement. Second, we calculate temporally principal displacement vector using histogram of displacement vectors. Temporally principal displacement vector indicates camera movement. Finally we eliminate clusters which have lower weight than threshold, and combine remained clusters for each pixel to generate multiple background clusters. Experimental results show that remained background model and detected moving object under camera moving.

MOVING OBJECT DETECTION FROM VIDEO CAPTURED BY MOVING SURVEILLANCE CAMERA

2021 ◽  
pp. 139-145
Author(s):  
Minh
Keyword(s):  
Object Detection ◽  
Template Matching ◽  
Moving Objects ◽  
Moving Object Detection ◽  
Object Motion ◽  
Moving Object ◽  
Camera Motion ◽  
Moving Camera ◽  
Image Differencing ◽  
Surveillance Camera

This paper presents an effective method for the detection of multiple moving objects from a video sequence captured by a moving surveillance camera. Moving object detection from a moving camera is difficult since camera motion and object motion are mixed. In the proposed method, we created a panoramic picture from a moving camera. After that, with each frame captured from this camera, we used the template matching method to found its place in the panoramic picture. Finally, using the image differencing method, we found out moving objects. Experimental results have shown that the proposed method had good performance with more than 80% of true detection rate on average.

scholarly journals Moving Object Detection from Moving Camera Image Sequences Using an Inertial Measurement Unit Sensor

2019 ◽  
Vol 10 (1) ◽  
pp. 268
Author(s):  
Sukwoo Jung ◽  
Youngmok Cho ◽  
Doojun Kim ◽  
Minho Chang
Keyword(s):  
Inertial Measurement Unit ◽  
Moving Objects ◽  
Image Sequences ◽  
Moving Object ◽  
Measurement Unit ◽  
Moving Camera ◽  
Inertial Measurement ◽  
Camera Image ◽  
Foreground Region ◽  
Harris Detector

This paper describes a new method for the detection of moving objects from moving camera image sequences using an inertial measurement unit (IMU) sensor. Motion detection systems with vision sensors have become a global research subject recently. However, detecting moving objects from a moving camera is a difficult task because of egomotion. In the proposed method, the interesting points are extracted by a Harris detector, and the background and foreground are classified by epipolar geometry. In this procedure, an IMU sensor is used to calculate the initial fundamental matrix. After the feature point classification, a transformation matrix is obtained from matching background feature points. Image registration is then applied to the consecutive images, and a difference map is extracted to find the foreground region. Finally, a minimum bounding box is applied to mark the detected moving object. The proposed method is implemented and tested with numerous real-world driving videos, which show that it outperforms the previous work.

Detection of moving objects with a moving camera using non-panoramic background model

2012 ◽  
Vol 24 (5) ◽  
pp. 1015-1028 ◽  
Author(s):  
Soo Wan Kim ◽  
Kimin Yun ◽  
Kwang Moo Yi ◽  
Sun Jung Kim ◽  
Jin Young Choi
Keyword(s):  
Moving Objects ◽  
Background Model ◽  
Moving Camera

Real-Time Structure Estimation in Dynamic Scenes Using a Single Camera

2013 ◽  
pp. 173-191
Author(s):  
Ashwin P. Dani ◽  
Zhen Kan ◽  
Nic Fischer ◽  
Warren E. Dixon
Keyword(s):  
Moving Objects ◽  
3D Structure ◽  
Estimation Algorithm ◽  
Unknown Input ◽  
Single Camera ◽  
Time Varying ◽  
Moving Camera ◽  
Structure Estimation ◽  
Modeling Uncertainties ◽  
Exponentially Stable

In this chapter, an online method is developed for estimating 3D structure (with proper scale) of moving objects seen by a moving camera. In contrast to traditionally developed batch solutions for this problem, a nonlinear unknown input observer strategy is used where the object’s velocity is considered as an unknown input to the perspective dynamical system. The estimator is exponentially stable, and hence, provides robustness against modeling uncertainties and measurement noise from the camera. The developed method provides first causal, observer based structure estimation algorithm for a moving camera viewing a moving object with unknown time-varying object velocities.

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