Robust Linear Auto-calibration of a Moving Camera from Image Sequences

2006 ◽  
pp. 71-80 ◽  
Author(s):  
Thorsten Thormählen ◽  
Hellward Broszio ◽  
Patrick Mikulastik
Keyword(s):  
Image Sequences ◽  
Moving Camera

scholarly journals General Moving Object Localization from a Single Flying Camera

2020 ◽  
Vol 10 (19) ◽  
pp. 6945
Author(s):  
Kin-Choong Yow ◽  
Insu Kim
Keyword(s):  
Prior Information ◽  
State Of The Art ◽  
Image Sequences ◽  
Specific Pattern ◽  
Visual Surveillance ◽  
Moving Object ◽  
Object Localization ◽  
Stationary Object ◽  
Open Spaces ◽  
Moving Camera

Object localization is an important task in the visual surveillance of scenes, and it has important applications in locating personnel and/or equipment in large open spaces such as a farm or a mine. Traditionally, object localization can be performed using the technique of stereo vision: using two fixed cameras for a moving object, or using a single moving camera for a stationary object. This research addresses the problem of determining the location of a moving object using only a single moving camera, and it does not make use of any prior information on the type of object nor the size of the object. Our technique makes use of a single camera mounted on a quadrotor drone, which flies in a specific pattern relative to the object in order to remove the depth ambiguity associated with their relative motion. In our previous work, we showed that with three images, we can recover the location of an object moving parallel to the direction of motion of the camera. In this research, we find that with four images, we can recover the location of an object moving linearly in an arbitrary direction. We evaluated our algorithm on over 70 image sequences of objects moving in various directions, and the results showed a much smaller depth error rate (less than 8.0% typically) than other state-of-the-art algorithms.

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.

Sign in / Sign up

Export Citation Format

Share Document