Browsing by Subject "Cameras"

Now showing 1 - 20 of 23

Open Access
Algebraic error analysis of collinear feature points for camera parameter estimation
(Elsevier, 2011-01-04) Urfalioglu, O.; Thormählen, T.; Broszio, H.; Mikulastik, P.; Çetin, A. Enis
In general, feature points and camera parameters can only be estimated with limited accuracy due to noisy images. In case of collinear feature points, it is possible to benefit from this geometrical regularity by correcting the feature points to lie on the supporting estimated straight line, yielding increased accuracy of the estimated camera parameters. However, regarding Maximum-Likelihood (ML) estimation, this procedure is incomplete and suboptimal. An optimal solution must also determine the error covariance of corrected features. In this paper, a complete theoretical covariance propagation analysis starting from the error of the feature points up to the error of the estimated camera parameters is performed. Additionally, corresponding Fisher Information Matrices are determined and fundamental relationships between the number and distance of collinear points and corresponding error variances are revealed algebraically. To demonstrate the impact of collinearity, experiments are conducted with covariance propagation analyses, showing significant reduction of the error variances of the estimated parameters.
Open Access
Attention-aware disparity control in interactive environments
(Springer, 2013) Celikcan, U.; Cimen, G.; Kevinc, E. B.; Capin, T.
Our paper introduces a novel approach for controlling stereo camera parameters in interactive 3D environments in a way that specifically addresses the interplay of binocular depth perception and saliency of scene contents. Our proposed Dynamic Attention-Aware Disparity Control (DADC) method produces depth-rich stereo rendering that improves viewer comfort through joint optimization of stereo parameters. While constructing the optimization model, we consider the importance of scene elements, as well as their distance to the camera and the locus of attention on the display. Our method also optimizes the depth effect of a given scene by considering the individual user's stereoscopic disparity range and comfortable viewing experience by controlling accommodation/convergence conflict. We validate our method in a formal user study that also reveals the advantages, such as superior quality and practical relevance, of considering our method. © 2013 Springer-Verlag Berlin Heidelberg.
Open Access
Autofocus method in thermal cameras based on image histogram
(IEEE, 2011) Turgay, E.; Teke, Oğuzhan
In this paper, a new histogram based auto-focusing method for thermal cameras is proposed. This proposed method is realized by FPGA (Field Programmable Gate Array) and DSP (Digital Signal Processor) working together and simultaneously. HF (High Frequency) component, obtained from real-time image flow by FPGA and DSP is used for auto-focusing process. Proposed method is able to determine the focus direction from the HF component produced in the process of histogram equalization by FPGA, unlike Fourier transform and pixel differenve based methods in the literature. With this superiority, proposed method requires no extra calculation for thermal cameras for which histogram equalization is necessary. Analysis show that proposed method is successful on the simulations and scanning thermal cameras.
Open Access
Automatic detection of salient objects and spatial relations in videos for a video database system
(Elsevier BV, 2008-10) Sevilmiş, T.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying. © 2008 Elsevier B.V. All rights reserved.
Open Access
Background subtraction with a moving camera
(IEEE, 2013) Topçu O.; Kalem, Aslıhan; Esen, E.
Moving object segmentation with a nonstationary camera is a difficult problem due to the motion of both camera and the object. A moving object segmentation method is proposed in this work to be used in pan-tilt-zoom (PTZ) cameras. The method is based on composing scene mosaic and applying Gaussian mixture background subtraction algorithm after constructing a background model using the mosaic. Background subtraction is performed by mapping the frames captured during camera's course of motion to the background mosaic. The proposed mosaic building method requires less number of picture correspondences when compared to known methods. The success of the proposed segmentation method is demonstrated by the conducted experiments. © 2013 IEEE.
Open Access
Camera tamper detection using wavelet analysis for video surveillance
(IEEE, 2007-09) Aksay, A.; Temizel, A.; Çetin, A. Enis
It is generally accepted that video surveillance system operators lose their concentration after a short period of time and may miss important events taking place. In addition, many surveillance systems are frequently left unattended. Because of these reasons, automated analysis of the live video feed and automatic detection of suspicious activity have recently gained importance. To prevent capture of their images, criminals resort to several techniques such as deliberately obscuring the camera view, covering the lens with a foreign object, spraying or defocusing the camera lens. In this paper, we propose some computationally efficient wavelet domain methods for rapid camera tamper detection and identify some real-life problems and propose solutions to these. © 2007 IEEE.
Open Access
Computer vision based method for real-time fire and flame detection
(Elsevier BV, 2006-01-01) Töreyin, B. U.; Dedeoǧlu, Y.; Güdükbay, Uğur; Çetin, A. Enis
This paper proposes a novel method to detect fire and/or flames in real-time by processing the video data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame and fire flicker is detected by analyzing the video in the wavelet domain. Quasi-periodic behavior in flame boundaries is detected by performing temporal wavelet transform. Color variations in flame regions are detected by computing the spatial wavelet transform of moving fire-colored regions. Another clue used in the fire detection algorithm is the irregularity of the boundary of the fire-colored region. All of the above clues are combined to reach a final decision. Experimental results show that the proposed method is very successful in detecting fire and/or flames. In addition, it drastically reduces the false alarms issued to ordinary fire-colored moving objects as compared to the methods using only motion and color clues. © 2005 Elsevier B.V. All rights reserved.
Open Access
Computer vision based unistroke keyboard system and mouse for the handicapped
(IEEE, 2003-07) Erdem, M .Erkut; Erdem, İ. Aykut; Atalay, Volkan; Çetin, A. Enis
In this paper, a unistroke keyboard based on computer vision is described for the handicapped. The keyboard can be made of paper or fabric containing an image of a keyboard, which has an upside down U-shape. It can even be displayed on a computer screen. Each character is represented by a non-overlapping rectangular region on the keyboard image and the user enters a character by illuminating a character region with a laser pointer. The keyboard image is monitored by a camera and illuminated key locations are recognized. During the text entry process the user neither have to turn the laser light off nor raise the laser light from the keyboard. A disabled person who has difficulty using his/her hands may attach the laser pointer to an eyeglass and easily enter text by moving his/her head to point the laser beam on a character location. In addition, a mouse-like device can be developed based on the same principle. The user can move the cursor by moving the laser light on the computer screen which is monitored by a camera. © 2003 IEEE.
Open Access
Contour based smoke detection in video using wavelets
(IEEE, 2006-09) Töreyin, B. Uğur; Dedeoğlu, Yiğithan; Çetin, A. Enis
This paper proposes a novel method to detect smoke in video. It is assumed the camera monitoring the scene is stationary. The smoke is semi-transparent at the early stages of a fire. Therefore edges present in image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene produce local extrema in the wavelet domain and a decrease in the energy content of these edges is an important indicator of smoke in the viewing range of the camera. Moreover, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries is also analyzed using a Hidden Markov model (HMM) mimicking the temporal behavior of the smoke. In addition, boundary of smoke regions are represented in wavelet domain and high frequency nature of the boundaries of smoke regions is also used as a clue to model the smoke flicker. All these clues are combined to reach a final decision.
Open Access
iki diferansiyel PIR algılayıcı ve bir kamera yardımıyla el hareketlerinin sınıflandırılması
(IEEE, 2014-04) Erden, Fatih; Bingol, A. S.; Çetin, A. Enis
Bu makalede, iki diferansiyel kızılberisi algılayıcı (PIR) ve bir kamera kullanılarak geliştirilen el jestleri algılama ve sınıflandırma sistemi tanıtılmaktadır. İzlenen alanda diferansiyel PIR algılayıcı dizisi ile hareket varlığı araştırılır. Bir hareket algılanması durumunda kamera yardımıyla söz konusu hareketin el olup olmadığına, el ise çok modlu sistem verilerinin birlikte değerlendirilmesiyle hareketin hangi tanımlı sınıfa ait olduğuna karar verilir. Kamera ile el jestleri algılama ve hareketleri sınıflandırma aşamasında ten algılama ve dışbükey zarf-gedik hesaplama yöntemleri kullanılır. Farklı el hareketlerinin PIR algılayıcı verileri yardımıyla sınıflandırılması Winner-Take-All (WTA) imza metoduyla gerçekleştirilir. Bu makalenin temel katkısı, WTA imza kodlarının tek boyutlu sinyallerin sınıflandırılmasında kullanılabileceğini ve çoklu algılayıcı tümleştirmesiyle jestleri tanıma sonuçlarının geliştirilebileceğini göstermektir.
Open Access
Introduction to the issue on emerging techniques in 3-D
(IEEE, 2012) Alatan, A. A.; Ostermann, J.; Onural, L.; AlRegib, G.; Mattoccia, S.; Yuan, C.
The fifteen papers in this special section that focus on three dimensional content (3D), with particular emphasis on the fusion of conventional camera outputs with those captured by other modalities, such as active sensors, multi-spectral data or dynamic range images as well as applications that support the measurement and improvement of 3-D content.
Open Access
Mobile image search using multi-query images
(IEEE, 2015) Çalışır, Fatih; Bastan, M.; Güdükbay, Uğur; Ulusoy, Özgür
Recent advances in mobile device technology have turned the mobile phones into powerfull devices with high resolution cameras and fast processing capabilities. Having more user interaction potential compared to regular PCs, mobile devices with cameras can enable richer content-based object image queries: the user can capture multiple images of the query object from different viewing angles and at different scales, thereby providing much more information about the object to improve the retrieval accuracy. The goal of this paper is to improve the mobile image retrieval performance using multiple query images. To this end, we use the well-known bag-of-visual-words approach to represent the images, and employ early and late fusion strategies to utilize the information in multiple query images. With extensive experiments on an object image dataset with a single object per image, we show that multi-image queries result in higher average precision performance than single image queries. © 2015 IEEE.
Open Access
A multi-modal video analysis approach for car park fire detection
(Elsevier, 2013) Verstockt, S.; Hoecke, S. V.; Beji, T.; Merci, B.; Gouverneur, B.; Çetin, A. Enis; Potter, P. D.; Walle, R. V. D.
In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%.
Open Access
A multi-sensor network for the protection of cultural heritage
(IEEE, 2011) Grammalidis, N.; Çetin, A. Enis; Dimitropoulos, K.; Tsalakanidou F.; Köse, Kıvanç; Günay, Osman; Gouverneur, B.; Torri, D.; Kuruoglu, E.; Tozzi, S.; Benazza, A.; Chaabane F.; Kosucu, B.; Ersoy, C.
The paper presents a novel automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire. Since these areas have been treasured and tended for very long periods of time, they are usually surrounded by old and valuable vegetation or situated close to forest regions, which exposes them to an increased risk of fire. The proposed system takes advantage of recent advances in multi-sensor surveillance technologies, using optical and infrared cameras, wireless sensor networks capable of monitoring different modalities (e.g. temperature and humidity) as well as local weather stations on the deployment site. The signals collected from these sensors are transmitted to a monitoring centre, which employs intelligent computer vision and pattern recognition algorithms as well as data fusion techniques to automatically analyze sensor information. The system is capable of generating automatic warning signals for local authorities whenever a dangerous situation arises, as well as estimating the propagation of the fire based on the fuel model of the area and other important parameters such as wind speed, slope, and aspect of the ground surface. © 2011 EURASIP.
Open Access
Online detection of fire in video
(IEEE, 2007) Töreyin, Behçet Uğur; Çetin, A. Enis
This paper describes an online learning based method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. Our fire detection method consists of weak classifiers based on temporal and spatial modeling of flames. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish temporal flame flicker process from motion of flame colored moving objects. Boundary of flames are represented in wavelet domain and high frequency nature of the boundaries of fire regions is also used as a clue to model the flame flicker spatially. Results from temporal and spatial weak classifiers based on flame flicker and irregularity of the flame region boundaries are updated online to reach a final decision. False alarms due to ordinary and periodic motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems.
Open Access
Real-time fire and flame detection in video
(IEEE, 2005) Dedeoğlu, Yigithan; Töreyin, B. Ugur; Güdükbay, Uğur; Çetin, A. Enis
This paper proposes a novel method to detect fire and/or flame by processing the video data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame and fire flicker is detected by analyzing the video in wavelet domain. Periodic behavior in flame boundaries is detected by performing temporal wavelet transform. Color variations in fire is detected by computing the spatial wavelet transform of moving fire-colored regions. Other clues used in the fire detection algorithm include irregularity of the boundary of the fire colored region and the growth of such regions in time. All of the above clues are combined to reach a final decision.
Open Access
Real-time smoke and flame detection in video
(IEEE, 2005) Töreyin, B. Uğur; Dedeoğlu, Yiğithan; Çetin, A. Enis
A novel method to detect smoke and/or flame by processing the video data generated by an ordinary camera monitoring a scene is proposed. It is assumed the camera is stationary. Since the smoke is semi-transparent, edges of image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. To determine the smoke, the background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. For the detection of flames, in addition to ordinary motion and color clues, flicker analysis is also carried out by analyzing the video in wavelet domain. These clues are combined to reach a final decision.
Open Access
A robust system for counting people using an infrared sensor and a camera
(Elsevier BV, 2015) Erden, F.; Alkar, A. Z.; Çetin, A. Enis
In this paper, a multi-modal solution to the people counting problem in a given area is described. The multi-modal system consists of a differential pyro-electric infrared (PIR) sensor and a camera. Faces in the surveillance area are detected by the camera with the aim of counting people using cascaded AdaBoost classifiers. Due to the imprecise results produced by the camera-only system, an additional differential PIR sensor is integrated to the camera. Two types of human motion: (i) entry to and exit from the surveillance area and (ii) ordinary activities in that area are distinguished by the PIR sensor using a Markovian decision algorithm. The wavelet transform of the continuous-time real-valued signal received from the PIR sensor circuit is used for feature extraction from the sensor signal. Wavelet parameters are then fed to a set of Markov models representing the two motion classes. The affiliation of a test signal is decided as the class of the model yielding higher probability. People counting results produced by the camera are then corrected by utilizing the additional information obtained from the PIR sensor signal analysis. With the proof of concept built, it is shown that the multi-modal system can reduce false alarms of the camera-only system and determines the number of people watching a TV set in a more robust manner.
Open Access
Searching for repeated video sequences
(ACM, 2007-09) Can, Tolga; Duygulu, Pınar
In this paper, we propose a new method to search different instances of a video sequence inside a long video and/or video collection. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. Results are provided on a full length feature movie, Run Lola Run and on commercials of TRECVID 2004 news video corpus. Copyright 2007 ACM.
Open Access
Video fire detection-Review
(Elsevier, 2013) Çetin, A. Enis; Dimitropoulos, K.; Gouverneur, B.; Grammalidis, N.; Günay, O.; Habiboğlu, Y. H.; Töreyin, B. U.; Verstockt, S.
This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation.