Search

Your search keyword '"Direkoglu, Cem"' showing total 114 results
Start Over Author "Direkoglu, Cem"
114 results on '"Direkoglu, Cem"'

8. Prediction of Daily Solar Irradiation Using CNN and LSTM Networks

Author

Vakitbilir, Nuray, Hilal, Adnan, Direkoğlu, Cem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo, editor, Babanli, Mustafa, editor, and Sadikoglu, Fahreddin M., editor

Published
2021
Full Text
View/download PDF

9. Review of Place Recognition Approaches: Traditional and Deep Learning Methods

Author

Taha, Mohammed Abdulghani, Şah, Melike, Direkoğlu, Cem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo, editor, Babanli, Mustafa, editor, and Sadikoglu, Fahreddin M., editor

Published
2021
Full Text
View/download PDF

10. Sea Turtle Species Classification for Environmental Research and Conservation

Author

Attal, Zafer, Direkoglu, Cem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo, editor, Babanli, Mustafa B., editor, and Sadikoglu, Fahreddin M., editor

Published
2020
Full Text
View/download PDF

11. Sea Turtle Detection Using Faster R-CNN for Conservation Purpose

Author

Badawy, Mohamed, Direkoglu, Cem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo, editor, Babanli, Mustafa B., editor, and Sadikoglu, Fahreddin M., editor

Published
2020
Full Text
View/download PDF

12. Evaluation of Image Representations for Player Detection in Field Sports Using Convolutional Neural Networks

Author

Şah, Melike, Direkoğlu, Cem, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo., editor, and Sadikoglu, Fahreddin M., editor

Published
2019
Full Text
View/download PDF

14. Feature extraction via heat flow analogy

Author

Direkoglu, Cem and Nixon, Mark

Subjects
005.3, QA75 Electronic computers. Computer science
Abstract

Feature extraction is an important field of image processing and computer vision. Features can be classified as low-level and high-level. Low-level features do not give shape information of the objects, where the popular low-level feature extraction techniques are edge detection, corner detection, thresholding as a point operation and optical flow estimation. On the other hand, high-level features give shape information, where the popular techniques are active contours, region growing, template matching and the Hough transform. In this thesis, we investigate the heat flow analogy, which is a physics based analogy, both for low-level and high-level feature extraction. Three different contributions to feature extraction, based on using the heat conduction analogy, are presented in this thesis. The solution of the heat conduction equation depends on properties of the material, the heat source as well as specified initial and boundary conditions. In our contributions, we consider and represent particular heat conduction problems, in the image and video domains, for feature extraction. The first contribution is moving-edge detection for motion analysis, which is a low-level feature extraction. The second contribution is shape extraction from images which is a high-level feature extraction. Finally, the third contribution is silhouette object feature extraction for recognition purpose and this can be considered as a combination of low-level and high-level feature extraction. Our evaluations and experimental results show that the heat analogy can be applied successfully both for low-level and for high-level feature extraction purposes in image processing and computer vision.

Published
2009

19. An Evaluation of Local Action Descriptors for Human Action Classification in the Presence of Occlusion

Author

Jargalsaikhan, Iveel, Direkoglu, Cem, Little, Suzanne, O’Connor, Noel E., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gurrin, Cathal, editor, Hopfgartner, Frank, editor, Hurst, Wolfgang, editor, Johansen, Håvard, editor, Lee, Hyowon, editor, and O’Connor, Noel, editor

Published
2014
Full Text
View/download PDF

21. Team Activity Recognition in Sports

Author

Direkoǧlu, Cem, O’Connor, Noel E., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Fitzgibbon, Andrew, editor, Lazebnik, Svetlana, editor, Perona, Pietro, editor, Sato, Yoichi, editor, and Schmid, Cordelia, editor

Published
2012
Full Text
View/download PDF

22. Shape Extraction Via Heat Flow Analogy

Author

Direkoğlu, Cem, Nixon, Mark S., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Blanc-Talon, Jacques, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2007
Full Text
View/download PDF

23. Low Level Moving-Feature Extraction Via Heat Flow Analogy

Author

Direkoğlu, Cem, Nixon, Mark S., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bebis, George, editor, Boyle, Richard, editor, Parvin, Bahram, editor, Koracin, Darko, editor, Remagnino, Paolo, editor, Nefian, Ara, editor, Meenakshisundaram, Gopi, editor, Pascucci, Valerio, editor, Zara, Jiri, editor, Molineros, Jose, editor, Theisel, Holger, editor, and Malzbender, Tom, editor

Published
2006
Full Text
View/download PDF

24. Retracted: Deep neural network‐based detection of pilgrims location in Holy Makkah.

Author

Taha, Mohammed Abdulghani, Direkoglu, Melike Sah, and Direkoglu, Cem

Subjects
TELECOMMUNICATION systems, PILGRIMS & pilgrimages, SCHOLARLY periodicals, INTERNATIONAL communication, INTERNET publishing
Abstract

Taha MA, Direkoglu MS, Direkoglu C. Deep neural network‐based detection of pilgrims location in Holy Makkah, International Journal of Communication Systems 2021, (https://doi.org/10.1002/dac.4792). The above article published online on 27 May 2021 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor and John Wiley and Sons Ltd. Following publication, it has come to our attention that the people named as the Guest Editors of the Special Issue were being impersonated by a fraudulent entity and the articles were not reviewed in line with the journal's peer review standards. The Editor has determined that the articles do not meet the required scholarly standards of the journal, and therefore has taken the decision to retract the article. We did not find any evidence of misconduct by the authors. The authors have been informed of the decision to retract. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

35. Abnormal crowd behavior detection using novel optical flow-based features

Author

Direkoglu, Cem, Sah, Melike, O'Connor, Noel E., Direkoglu, Cem, Sah, Melike, and O'Connor, Noel E.

Abstract

In this paper, we propose a novel optical flow based features for abnormal crowd behaviour detection. The proposed feature is mainly based on the angle difference computed between the optical flow vectors in the current frame and in the previous frame at each pixel location. The angle difference information is also combined with the optical flow magnitude to produce new, effective and direction invariant event features. A one-class SVM is utilized to learn normal crowd behavior. If a test sample deviates significantly from the normal behavior, it is detected as abnormal crowd behavior. Although there are many optical flow based features for crowd behaviour analysis, this is the first time the angle difference between optical flow vectors in the current frame and in the previous frame is considered as a anomaly feature. Evaluations on UMN and PETS2009 datasets show that the proposed method performs competitive results compared to the state-of-the-art methods.

Published
2017

38. Reduction of false alarms triggered by spiders/cobwebs in surveillance camera networks.

Author

Hebbalaguppe, Ramya, McGuinness, Kevin, Kuklyte, Jogile, Albatal, Rami, Direkoglu, Cem, O'Connor, Noel E., Hebbalaguppe, Ramya, McGuinness, Kevin, Kuklyte, Jogile, Albatal, Rami, Direkoglu, Cem, and O'Connor, Noel E.

Abstract

The percentage of false alarms caused by spiders in automated surveillance can range from 20-50%. False alarms increase the workload of surveillance personnel validating the alarms and the maintenance labor cost associated with regular cleaning of webs. We propose a novel, cost effective method to detect false alarms triggered by spiders/webs in surveillance camera networks. This is accomplished by building a spider classifier intended to be a part of the surveillance video processing pipeline. The proposed method uses a feature descriptor obtained by early fusion of blur and texture. The approach is sufficiently efficient for real-time processing and yet comparable in performance with more computationally costly approaches like SIFT with bag of visual words aggregation. The proposed method can eliminate 98.5% of false alarms caused by spiders in a data set supplied by an industry partner, with a false positive rate of less than 1%

Published
2016
Full Text
View/download PDF

39. SAVASA project @ TRECVid 2013: semantic indexing and interactive surveillance event detection

Author

Little, Suzanne, Jargalsaikhan, Iveel, Albatal, Rami, Direkoglu, Cem, O'Connor, Noel E., Smeaton, Alan F., Clawson, Kathy, Jing, Min, Scotney, Bryan, Wang, Hui, Li, Jun, Nieto, Marcos, Ortega, Juan Diego, Rodriguez, Aitor, Aramburu, Inigo, and Kafetzakis, Emmanouil

Subjects
Semantic indexing, Surveillance event detection, SAVASA, Machine learning, Digital video, Information retrieval, Multimedia systems
Abstract

In this paper we describe our participation in the semantic indexing (SIN) and interactive surveillance event detection (SED) tasks at TRECVid 2013 [11]. Our work was motivated by the goals of the EU SAVASA project (Standards-based Approach to Video Archive Search and Analysis) which supports search over multiple video archives. Our aims were: to assess a standard object detection methodology (SIN); evaluate contrasting runs in automatic event detection (SED) and deploy a distributed, cloud-based search interface for the interactive component of the SED task. Results from the SIN task, underlying retrospective classifiers for the surveillance event detection and a discussion of the contrasting aims of the SAVASA user interface compared with the TRECVid task requirements are presented.

Published
2013

40. Player detection in field sports.

Author

Direkoglu, Cem, Sah, Melike, and O’Connor, Noel E.

Subjects
*PATTERN recognition systems, *ATHLETIC fields, *FEATURE extraction, *IMAGE processing, *HEAT equation, *FOURIER transforms
Abstract

We describe a method for player detection in field sports with a fixed camera setup based on a new player feature extraction strategy. The proposed method detects players in static images with a sliding window technique. First, we compute a binary edge image and then the detector window is shifted over the edge regions. Given a set of binary edges in a sliding window, we introduce and solve a particular diffusion equation to generate a shape information image. The proposed diffusion to generate a shape information image is the key stage and the main theoretical contribution in our new algorithm. It removes the appearance variations of an object while preserving the shape information. It also enables the use of polar and Fourier transforms in the next stage to achieve scale- and rotation-invariant feature extraction. A support vector machine classifier is used to assign either player or non-player class inside a detector window. We evaluate our approach on three different field hockey datasets. In general, results show that the proposed feature extraction is effective and performs competitive results compared to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Published
2018
Full Text
View/download PDF

41. Team behaviour analysis in sports using the poisson equation

Author

Direkoglu, Cem and O'Connor, Noel E.

Subjects
Image processing
Abstract

We propose a novel physics-based model for analysing team play- ers’ positions and movements on a sports playing field. The goal is to detect for each frame the region with the highest population of a given team’s players and the region towards which the team is moving as they press for territorial advancement, termed the region of intent. Given the positions of team players from a plan view of the playing field at any given time, we solve a particular Poisson equation to generate a smooth distribution. The proposed distribu- tion provides the likelihood of a point to be occupied by players so that more highly populated regions can be detected by appropriate thresholding. Computing the proposed distribution for each frame provides a sequence of distributions, which we process to detect the region of intent at any time during the game. Our model is evalu- ated on a field hockey dataset, and results show that the proposed approach can provide effective features that could be used to gener- ate team statistics useful for performance evaluation or broadcasting purposes.

Published
2012

42. On Using Physical Analogies for Feature and Shape Extraction in Computer Vision

Author

Nixon, Mark, Liu, Xin, Direkoglu, Cem, and Hurley, David

Abstract

There is a rich literature of approaches to image feature extraction in computer vision. Many sophisticated approaches exist for low- and for high-level feature extraction but can be complex to implement with parameter choice guided by experimentation, but with performance analysis and optimization impeded by speed of computation. We have developed new feature extraction techniques on notional use of physical paradigms, with parametrization aimed to be more familiar to a scientifically trained user, aiming to make best use of computational resource. This paper is the first unified description of these new approaches, outlining the basis and results that can be achieved. We describe how gravitational force can be used for low-level analysis, while analogies of water flow and heat can be deployed to achieve high-level smooth shape detection, by determining features and shapes in a selection of images, comparing results with those by stock approaches from the literature. We also aim to show that the implementation is consistent with the original motivations for these techniques and so contend that the exploration of physical paradigms offers a promising new avenue for new approaches to feature extraction in computer vision.

Published
2011

43. Moving-edge detection via heat flow analogy

Author

Direkoglu, Cem and Nixon, Mark

Abstract

In this paper, a new and automatic moving-edge detection algorithm is proposed, based on using the heat flow analogy. This algorithm starts with anisotropic heat diffusion in the spatial domain, to remove noise and sharpen region boundaries for the purpose of obtaining high quality edge data. Then, isotropic and linear heat diffusion is applied in the temporal domain to calculate the total amount of heat flow. The moving-edges are represented as the total amount of heat flow out from the reference frame. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain binary moving edges. Evaluation, on a variety of data, indicates that this approach can handle noise in the temporal domain because of the averaging inherent of isotropic heat flow. Results also show that this technique can detect moving-edges in image sequences, without background image subtraction.

Published
2011

44. An information retrieval approach to identifying infrequent events in surveillance video

Author

Little, Suzanne, Jargalsaikhan, Iveel, Clawson, Kathy, Li, Hao, Nieto, Marcos, Direkoglu, Cem, O'Connor, Noel E., Smeaton, Alan F., Liu, Jun, Scotney, Bryan, Wang, Hui, Little, Suzanne, Jargalsaikhan, Iveel, Clawson, Kathy, Li, Hao, Nieto, Marcos, Direkoglu, Cem, O'Connor, Noel E., Smeaton, Alan F., Liu, Jun, Scotney, Bryan, and Wang, Hui

Abstract

This paper presents work on integrating multiple computer vision-based approaches to surveillance video analysis to support user retrieval of video segments showing human activities. Applied computer vision using real-world surveillance video data is an extremely challenging research problem, independently of any information retrieval (IR) issues. Here we describe the issues faced in developing both generic and specific analysis tools and how they were integrated for use in the new TRECVid interactive surveillance event detection task. We present an interaction paradigm and discuss the outcomes from face-to-face end user trials and the resulting feedback on the system from both professionals, who manage surveillance video, and computer vision or machine learning experts. We propose an information retrieval approach to finding events in surveillance video rather than solely relying on traditional annotation using specifically trained classifiers.

Published
2013

45. Action recognition based on sparse motion trajectories

Author

Jargalsaikhan, Iveel, Little, Suzanne, Direkoglu, Cem, O'Connor, Noel E., Jargalsaikhan, Iveel, Little, Suzanne, Direkoglu, Cem, and O'Connor, Noel E.

Abstract

We present a method that extracts effective features in videos for human action recognition. The proposed method analyses the 3D volumes along the sparse motion trajectories of a set of interest points from the video scene. To represent human actions, we generate a Bag-of-Features (BoF) model based on extracted features, and finally a support vector machine is used to classify human activities. Evaluation shows that the proposed features are discriminative and computationally efficient. Our method achieves state-of-the-art performance with the standard human action recognition benchmarks, namely KTH and Weizmann datasets.

Published
2013

46. SAVASA project @ TRECVID 2012: interactive surveillance event detection

Author

Little, Suzanne, Jargalsaikhan, Iveel, Clawson, Kathy, Li, Hao, Nieto, Marcos, Direkoglu, Cem, O'Connor, Noel E., Smeaton, Alan F., Rodriguez, Aitor, Sanchez, Pedro, Villarroel Peniza, Karina, Martínez Llorens, Ana, Giménez, Roberto, Santos de la Cámara, Raúl, Mereu, Anna, Little, Suzanne, Jargalsaikhan, Iveel, Clawson, Kathy, Li, Hao, Nieto, Marcos, Direkoglu, Cem, O'Connor, Noel E., Smeaton, Alan F., Rodriguez, Aitor, Sanchez, Pedro, Villarroel Peniza, Karina, Martínez Llorens, Ana, Giménez, Roberto, Santos de la Cámara, Raúl, and Mereu, Anna

Abstract

In this paper we describe our participation in the interactive surveillance event detection task at TRECVid 2012. The system we developed was comprised of individual classifiers brought together behind a simple video search interface that enabled users to select relevant segments based on down~sampled animated gifs. Two types of user -- `experts' and `end users' -- performed the evaluations. Due to time constraints we focussed on three events -- ObjectPut, PersonRuns and Pointing -- and two of the five available cameras (1 and 3). Results from the interactive runs as well as discussion of the performance of the underlying retrospective classifiers are presented.

Published
2012

47. Skeleton Extraction via Anisotropic Heat Flow

Author

Direkoglu, Cem, Dahyot, Rozenn, Manzke, Michael, Direkoglu, Cem, Dahyot, Rozenn, and Manzke, Michael

Abstract

We introduce a novel skeleton extraction algorithm in binary and gray-scale images, based on the anisotropic heat diffusion analogy. We propose to diffuse image in the dominance of direction normal to the feature boundaries and also allow tangential diffusion to contribute slightly. The proposed anisotropic diffusion provides a high quality medial function in the image, since it removes noise and preserves prominent curvatures of the shape along the level-sets (skeleton locations). Then the skeleton strength map, which provides the likelihood to be a skeleton point, is obtained by computing the mean curvature of level-sets. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain thin and binary skeleton. Results indicate that this approach has advantages in handling noise in the image and in obtaining smooth shape skeleton because of the directional averaging inherent of our new anisotropic heat flow.

Published
2010

49. Interactive surveillance event detection at TRECVid2012

Author

Little, Suzanne, primary, Jargalsaikhan, Iveel, additional, Clawson, Kathy, additional, Nieto, Marcos, additional, Li, Hao, additional, Direkoglu, Cem, additional, O'Connor, Noel E., additional, Smeaton, Alan F., additional, Liu, Jun, additional, Scotney, Bryan, additional, Wang, Hui, additional, Gaines, Seán, additional, Rodriguez, Aitor, additional, Sanchez, Pedro, additional, Martínez Llorens, Ana, additional, Villarroel Peniza, Karina, additional, Gimenez, Roberto, additional, Santos de La Cámara, Raúl, additional, Mereu, Anna, additional, Prados, Celso, additional, and Kafetzakis, Emmanouil, additional

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results