Video Stabilization for a Camcorder Mounted on a Moving Vehicle

We introduce a novel video stabilization method that enables the extraction of optic flow from short unstable sequences. Contrary to traditional stabilization techniques that use approximative global motion models to estimate the full camera motion, our method estimates the unstable component of the camera motion only. This allows for the use of simpler global motion models, and at the same time extends the validity to more complex environments, such as close scenes that contain independently moving objects. The unstable component of the camera motion is derived from a maximization of the temporal local velocity constancy over the entire short sequence. The method, embedded within a phase-based optic flow algorithm, is tested on both synthetic and complex real-world sequences. The optic flow obtained using our technique is denser than that extracted directly from the original sequence, and from a sequence stabilized with a more traditional stabilization technique.

show abstract

“…The desired changes are computed for each pixel, orientation and frame using Eq. (6). Note that, similar to the temporal phase gradient (Eq.…”

Section: Temporal Phase Gradient Linearizationmentioning

confidence: 93%

Optic flow from unstable sequences through local velocity constancy maximization

Pauwels

Hulle

2009

Image and Vision Computing

View full text Add to dashboard Cite

show abstract

“…Rail tracks are aligned parallel to each other and their width decrease linearly in the image from bottom to up. Vanishing point term refers to the intersection of the track lines defined as in Liang [33]. It is firstly performed color conversion from RGB to HSV color space in this algorithm.…”

Section: Switch Detection Methodsmentioning

confidence: 99%

A Vision Based Condition Monitoring Approach for Rail Switch and Level Crossing using Hierarchical SVM in Railways

Taştimur

Karaköse

Akın

2016

International Journal of Applied Mathematics, Electronics and Computers

View full text Add to dashboard Cite

Rail track, turnout and level crossing are critical parts of railway components. So faults of rail surface are directly related to the operation safety. The defects occurring in switches can lead to accidents and the derailment of the train. Therefore, it is necessary to utilize advanced technology to monitor rail damage of the switch and level crossing zones. In this study, the switch and level crossing detection are performed with vision based contactless image processing techniques. Edge detection algorithm, image processing filters, morphological feature extraction, Hough transform and hierarchical SVM classifier are utilized to detect turnout and level crossing regions in the railway images. While switch points are detected, images of the area in front of the train are continuously taken from camera placed on the train. These images contain foreign objects such as buildings, trees, etc. The foreign objects existing in the railway image make it difficult to detect accurately the rail track. The turnout and level crossing detection cannot also be performed using the information of the rail track that cannot be correctly detected. The several processes, such as some image processing filters and morphological feature extraction, have been performed to solve this problem. With destroying the foreign objects from the railway images, both the accuracy rate of the proposed method has been increased and real-time implementation of the method is provided. The Hough transform is utilized to detect rail track, switch and level crossing in the proposed method. The turnout detection is performed by applying SVM classifier to railway image. The proposed method provides real-time rail track, level crossing and turnout detection. Furthermore, this method has gained dynamic feature due to not be utilized any template image for switch detection. When evaluated from these aspects, both the proposed method is superior to other methods in literature and results were obtained in a shorter time thanks to applying ROI Segmentation to the railway image.

show abstract

“…Jirawimut et al [11] use stereo cameras as an odometer for blind or visually impaired pedestrians. Liang et al [18] improve the stability of the images captured by video cameras mounted on vehicles for intelligent driver-assistance systems. Miura et al [22] use computer vision to assist drivers in responding to traffic conditions.…”

Section: Navigation Using Images and Videosmentioning

confidence: 99%

Multimedia for mobile environment: image enhanced navigation

et al. 2006

View full text Add to dashboard Cite

As mobile systems (such as laptops and mobile telephones) continue growing, navigation assistance and location-based services are becoming increasingly important. Existing technology allow mobile users to access Internet services (e.g. email and web surfing), simple multimedia services (e.g. music and video clips), and make telephone calls. However, the potential of advanced multimedia services has not been fully developed, especially multimedia for navigation or location based services.At Purdue University, we are developing an image database, known as LAID, in which every image is annotated with its location, compass heading, acquisition time, and weather conditions. LAID can be used to study several types of navigation problems: A mobile user can take an image and transmit the image to the LAID sever. The server compares the image with the images stored in the database to determine where the user is located. We refer to this as the "forward" navigation problem. The second type of problem is to provide a "virtual tour on demand." A user inputs a starting and an ending addresses and LAID retrieves the images along a route that connects the two addresses. This is a generalization of route planning. Our database currently contains over 20000 images and covers approximately 25% of the city of West Lafayette, Indiana.

show abstract

Video Stabilization for a Camcorder Mounted on a Moving Vehicle

Cited by 76 publications

References 30 publications

Optic flow from unstable sequences through local velocity constancy maximization

Optic flow from unstable sequences through local velocity constancy maximization

A Vision Based Condition Monitoring Approach for Rail Switch and Level Crossing using Hierarchical SVM in Railways

Multimedia for mobile environment: image enhanced navigation

Contact Info

Product

Resources

About