Aytul Ercil
Sabanci University, EECS, Faculty Member
In this paper, we introduce a revolutionary interaction framework that is based on the idea of around device interaction. The proposed method constitutes a touch-less data entry system that is based on the interaction between the magnetic... more
In this paper, we introduce a revolutionary interaction framework that is based on the idea of around device interaction. The proposed method constitutes a touch-less data entry system that is based on the interaction between the magnetic fields around a device and a magnet. The magnetic field that surrounds the device is generated by a magnetic sensor (compass) that is embedded in the new generation of mobile phones. The movements of a permanent magnet in front of the device deforms the sensor’s original magnetic field pattern whereby we can constitute a new means of communication between the user and the device. Thus, the magnetic field encompassing the device plays the role of a communication channel and encodes the hand-movement patterns of the user into temporal changes of the sensor’s magnetic field. In the back-end of the communication, an engine samples the momentary status of the field during a trial and recognizes the user’s pattern by matching it against some pre-recorded templates. The proposed method has been tested in a variety of applications (such as micro-interaction, handwriting recognition, user authentication, etc) and concluded in very promising results.
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Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 2005
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Research Interests: Engineering, Computer Science, Algorithms, Artificial Intelligence, Computer Vision, and 15 moreMedical Imaging, Image Analysis, Medical Image Analysis, Image segmentation, Learning, Cars, Computational Imaging, Edge Detection, Character Segmentation, Active Contour, Kernel Density Estimation, Density Estimation, Basal ganglia, Image Generation, and Kernel density estimate
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Abstract Real-time rendering of large animated crowds consisting of thousands of virtual humans is important for several applications including simulations, games, and interactive walkthroughs but cannot be performed using complex... more
Abstract Real-time rendering of large animated crowds consisting of thousands of virtual humans is important for several applications including simulations, games, and interactive walkthroughs but cannot be performed using complex polygonal models at interactive frame rates. For that reason, methods using large numbers of precomputed image-based representations, called impostors, have been proposed. These methods take advantage of existing programmable graphics hardware to compensate for computational expense ...
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Research Interests: Engineering, Computer Science, Algorithms, Artificial Intelligence, Magnetic Resonance Imaging, and 15 moreAdolescent, Image segmentation, Brain, Humans, Child, Female, Magnetic Resonance, Active Contour, Artifacts, Human Brain, Aged, Adult, Basal ganglia, Magnetic resonance image, and Kernel density estimate
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Emerging cost-efficient depth sensor technologies reveal new possibilities to cope with difficulties in action recognition. Depth information improves the quality of skeleton detec- tion process, hence, pose estimation can be done more... more
Emerging cost-efficient depth sensor technologies reveal new possibilities to cope with difficulties in action recognition. Depth information improves the quality of skeleton detec- tion process, hence, pose estimation can be done more efficiently. Recently many studies fo- cus on temporal analyses over estimated skeleton poses to recognize actions. In this paper we have an inclusive study of the spatiotemporal kinematic features and propose an action recognition framework with feature selection capability to deal with the multitudinous of features by leveraging data mining capabilities of random decision forests. We describe human motion via a rich collection of kinematic feature time-series computed from the skel- etal representation of the body in motion. We discriminatively optimize a random decision forest model over this collection to identify the most effective subset of features, localized both in time and space. Later, we train a support vector machine classifier on the sel...
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Abstract In this paper, we introduce a revolutionary interaction framework that is based on the idea of around device interaction. The proposed method constitutes a touch-less data entry system that is based on the interaction between the... more
Abstract In this paper, we introduce a revolutionary interaction framework that is based on the idea of around device interaction. The proposed method constitutes a touch-less data entry system that is based on the interaction between the magnetic fields around a device and a magnet. The magnetic field that surrounds the device is generated by a magnetic sensor (compass) that is embedded in the new generation of mobile phones. The movements of a permanent magnet in front of the device deforms the sensor's original ...
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Although algebraic or so-called “implicit polynomial ” curves have been studied rather extensively for several decades, to the best of our knowledge, a dynamic formulation of them, similar to active contours, has not been done yet. This... more
Although algebraic or so-called “implicit polynomial ” curves have been studied rather extensively for several decades, to the best of our knowledge, a dynamic formulation of them, similar to active contours, has not been done yet. This paper develops a dynamic formulation for implicit polynomial curves based on level set formalism. In particular, it is shown that utilization of an implicit polynomial distance function in the level set equation yields an ordinary differential equation (ODE) for the temporal behavior of the polynomial coefficients. Using a control theoretic approach, several problems such as curve morphing, dynamic conic fitting without and with constraint, i.e. dynamic ellipse fit, and dynamic curve fitting can be tackled within this new framework. Results are verified by several examples on real images. 1
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Advances in the medical imaging technology has lead to an exponential growth in the number of digital images that needs to be acquired, analyzed, classified, stored and retrieved in medical centers. As a result, medical image... more
Advances in the medical imaging technology has lead to an exponential growth in the number of digital images that needs to be acquired, analyzed, classified, stored and retrieved in medical centers. As a result, medical image classification and retrieval has recently gained high interest in the scientific community. Despite several attempts, such as the yearly-held ImageCLEF Medical Image Annotation Competition, the proposed solutions are still far from being sufficiently accurate for real-life implementations. In this paper we summarize the technical details of our experiments for the Im-ageCLEF 2009 medical image annotation task. We use a direct and two hierarchical classification schemes that employ support vector machines and local binary patterns, which are recently developed low-cost texture descriptors. The direct scheme employs a single SVM to automatically annotate X-ray images. The two proposed hierarchi-cal schemes divide the classification task into sub-problems. The fir...
Research Interests: Computer Science, Image Processing, Evaluation, Performance, Support Vector Machines, and 11 moreX-ray imaging, Content based image retrieval, Medical Image Retrieval, Support vector machine, Image Search and Retrieval, Medical Image, Local Binary Pattern, Exponential Growth, Digital Image, Automatic Annotation, and Medical Image Annotation
In this paper, a new method based on the use of wavelet transformation prior to independent component analysis for solving the problem of defect detection in textile fabric images is presented. Different sub-bands of the wavelet packet... more
In this paper, a new method based on the use of wavelet transformation prior to independent component analysis for solving the problem of defect detection in textile fabric images is presented. Different sub-bands of the wavelet packet tree scheme of the defect-free sub-windows are obtained and independent components of these subbands are calculated as the basis vectors. The true feature vectors corresponding to these basis vectors are computed. The test sub-window is labeled as defective or not according to the Euclidean distance between the true feature vector representing the non-defective regions and the feature vector of the sub-window under test. The advantage of adding wavelet analysis prior to independent component analysis is presented. 1.
Tracking free form objects by fitting curve models to their boundaries in real-time is not feasible due to the computational burden of fitting algorithms. In this paper, we propose to do fitting only for certain frames in an image... more
Tracking free form objects by fitting curve models to their boundaries in real-time is not feasible due to the computational burden of fitting algorithms. In this paper, we propose to do fitting only for certain frames in an image sequence and fill in the missing ones using Kalman filtering technique. An algorithm is presented to track a free-form shaped object, moving along an unknown trajectory, within the camera’s field of view (FOV). A discrete steady-state Kalman filter is used to estimate the future positions and orientation of the target object. Kalman filter uses the “related points ” extracted from the decomposition of implicit polynomials of target’s boundary curves and measured position of target’s centroid. Related points undergo the same motion with the curve, hence could be used to estimate the orientation of the target. The resulting algorithm is verified with simulations. 1.
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We prop ose a shape and data driven texture segmentation method using loca l binary patterns (LBP) and active contours. In particular, we pass textured images through a new LBP-based filter, which produces non-textured images. In this... more
We prop ose a shape and data driven texture segmentation method using loca l binary patterns (LBP) and active contours. In particular, we pass textured images through a new LBP-based filter, which produces non-textured images. In this “filtered ” doma in each textured region of the original imag e exhibits a characteristic intensity distribution. In this domain we pose the segmentation problem as an optimization problem in a Bayesian framework. The cost functional contains a data-driven term, as well as a term that b ring s in information about the shapes of the objects to be segmented. We solve the optimization problem u sing level set-based active contours. Our experimental results on synthetic and real textures demonstrate the effectiveness of our approach in segmenting challenging textures as well as its robustness to missing data and occlusions.
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In this paper, a novel method for texture defect detection is presented. The method makes use of Independent Component Analysis (ICA) for feature extraction from the nonoverlapping subwindows of texture images and classifies a subwindow... more
In this paper, a novel method for texture defect detection is presented. The method makes use of Independent Component Analysis (ICA) for feature extraction from the nonoverlapping subwindows of texture images and classifies a subwindow as defective or nondefective according to Euclidean distance between the feature obtained from average value of the features of a defect free sample and the feature obtained from one subwindow of a test image. The experimental results demonstrating the use of this method for visual inspection of textile products obtained from a real factory environment are also presented.
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In this paper, the three-, the six-, and the eight-parameter two-dimensional gradient based adaptive lattice filters are compared in the context of defect detection in textures corresponding to textile fabrics. A novel histogram... more
In this paper, the three-, the six-, and the eight-parameter two-dimensional gradient based adaptive lattice filters are compared in the context of defect detection in textures corresponding to textile fabrics. A novel histogram modification technique is also applied for preprocessing the gray level texture image. Moreover, with the proposed scheme, it is possible to detect defects in an unsupervised manner
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In this research, we propose a novel parallelizable architecture for the optimization of various sound synthesis parameters. The architecture employs genetic algorithms to match the parameters of different sound synthesizer topologies to... more
In this research, we propose a novel parallelizable architecture for the optimization of various sound synthesis parameters. The architecture employs genetic algorithms to match the parameters of different sound synthesizer topologies to target sounds. The fitness function is evaluated in parallel to decrease its convergence time. Based on the proposed architecture, we have implemented a framework using the SuperCollider audio synthesis and programming environment and conducted several experiments.
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Reconstruction of archaeological finds from fragments, is a tedious task requiring many hours of work from the archaeologists and restoration personnel. In this paper we present a framework for the full reconstruction of the original... more
Reconstruction of archaeological finds from fragments, is a tedious task requiring many hours of work from the archaeologists and restoration personnel. In this paper we present a framework for the full reconstruction of the original objects using texture and surface design information on the sherd. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. The confidence of this process is also defined. Feature values are derived from these original and predicted images of ...
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In this chapter, we present data collection activities and preliminary research findings from the real-world database collected with “UYANIK,” a passenger car instrumented with several sensors, CAN-Bus data logger, cameras, microphones,... more
In this chapter, we present data collection activities and preliminary research findings from the real-world database collected with “UYANIK,” a passenger car instrumented with several sensors, CAN-Bus data logger, cameras, microphones, data acquisitions systems, computers, and support systems. Within the shared frameworks of Drive-Safe Consortium (Turkey) and the NEDO (Japan) International Collaborative Research on Driving Behavior Signal Processing, close to 16 TB of driver behavior, vehicular, and road data have been ...
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Future’s environments will be sensitive and responsive to the presence of people to support them carrying out their everyday life activities, tasks and rituals, in an easy and natural way. Such interactive spaces will use the information... more
Future’s environments will be sensitive and responsive to the presence of people to support them carrying out their everyday life activities, tasks and rituals, in an easy and natural way. Such interactive spaces will use the information and communication technologies to bring the computation into the physical world, in order to enhance ordinary activities of their users. This paper describes a speech-based spoken multimedia retrieval system that can be used to present relevant video-podcast (vodcast) footage, in response to spontaneous speech and conversations during daily life activities. The proposed system allows users to search the spoken content of multimedia files rather than their associated meta-information and let them navigate to the right portion where queried words are spoken by facilitating within-medium searches of multimedia content through a bag-of-words approach. Finally, we have studied the proposed system on different scenarios by using vodcasts in English from various categories, as the targeted multimedia, and discussed how it would enhance people’s everyday life activities by different scenarios including education, entertainment, marketing, news and workplace.