| 1. |
- Afzal, Hassan, et al.
(författare)
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Full 3D Reconstruction of Non-Rigidly Deforming Objects
- 2018
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Ingår i: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 14:1s
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we discuss enhanced full 360 degrees 3D reconstruction of dynamic scenes containing non-rigidly deforming objects using data acquired from commodity depth or 3D cameras. Several approaches for enhanced and full 3D reconstruction of non-rigid objects have been proposed in the literature. These approaches suffer from several limitations due to requirement of a template, inability to tackle large local deformations and topology changes, inability to tackle highly noisy and low-resolution data, and inability to produce online results. We target online and template-free enhancement of the quality of noisy and low-resolution full 3D reconstructions of dynamic non-rigid objects. For this purpose, we propose a view-independent recursive and dynamic multi-frame 3D super-resolution scheme for noise removal and resolution enhancement of 3D measurements. The proposed scheme tracks the position and motion of each 3D point at every timestep by making use of the current acquisition and the result of the previous iteration. The effects of system blur due to per-point tracking are subsequently tackled by introducing a novel and efficient multi-level 3D bilateral total variation regularization. These characteristics enable the proposed scheme to handle large deformations and topology changes accurately. A thorough evaluation of the proposed scheme on both real and simulated data is carried out. The results show that the proposed scheme improves upon the performance of the state-of-the-art methods and is able to accurately enhance the quality of low-resolution and highly noisy 3D reconstructions while being robust to large local deformations.
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| 2. |
- Al Ismaeil, Kassem, et al.
(författare)
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Bilateral Filter Evaluation Based on Exponential Kernels
- 2012
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Konferensbidrag (refereegranskat)abstract
- The well-known bilateral filter is used to smooth noisy images while keeping their edges. This filter is commonly used with Gaussian kernel functions without real justification. The choice of the kernel functions has a major effect on the filter behavior. We propose to use exponential kernels with L1 distances instead of Gaussian ones. We derive Stein's Unbiased Risk Estimate to find the optimal parameters of the new filter and compare its performance with the conventional one. We show that this new choice of the kernels has a comparable smoothing effect but with sharper edges due to the faster, smoothly decaying kernels.
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| 3. |
- Bahnsen, Alejandro Correa, et al.
(författare)
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Example-dependent cost-sensitive decision trees
- 2015
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Ingår i: Expert systems with applications. - : Elsevier BV. - 0957-4174 .- 1873-6793. ; 42:19, s. 6609-6619
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Tidskriftsartikel (refereegranskat)abstract
- Several real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples. However, standard classification methods do not take these costs into account, and assume a constant cost of misclassification errors. State-of-the-art example-dependent cost-sensitive techniques only introduce the cost to the algorithm, either before or after training, therefore, leaving opportunities to investigate the potential impact of algorithms that take into account the real financial example-dependent costs during an algorithm training. In this paper, we propose an example-dependent cost-sensitive decision tree algorithm, by incorporating the different example-dependent costs into a new cost-based impurity measure and a new cost-based pruning criteria. Then, using three different databases, from three real-world applications: credit card fraud detection, credit scoring and direct marketing, we evaluate the proposed method. The results show that the proposed algorithm is the best performing method for all databases. Furthermore, when compared against a standard decision tree, our method builds significantly smaller trees in only a fifth of the time, while having a superior performance measured by cost savings, leading to a method that not only has more business-oriented results, but also a method that creates simpler models that are easier to analyze.
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| 4. |
- Bahnsen, Alejandro Correa, et al.
(författare)
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Feature engineering strategies for credit card fraud detection
- 2016
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Ingår i: Expert systems with applications. - : Elsevier BV. - 0957-4174 .- 1873-6793. ; 51, s. 134-142
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Tidskriftsartikel (refereegranskat)abstract
- Every year billions of Euros are lost worldwide due to credit card fraud. Thus, forcing financial institutions to continuously improve their fraud detection systems. In recent years, several studies have proposed the use of machine learning and data mining techniques to address this problem. However, most studies used some sort of misclassification measure to evaluate the different solutions, and do not take into account the actual financial costs associated with the fraud detection process. Moreover, when constructing a credit card fraud detection model, it is very important how to extract the right features from the transactional data. This is usually done by aggregating the transactions in order to observe the spending behavioral patterns of the customers. In this paper we expand the transaction aggregation strategy, and propose to create a new set of features based on analyzing the periodic behavior of the time of a transaction using the von Mises distribution. Then, using a real credit card fraud dataset provided by a large European card processing company, we compare state-of-the-art credit card fraud detection models, and evaluate how the different sets of features have an impact on the results. By including the proposed periodic features into the methods, the results show an average increase in savings of 13%. (C) 2016 Elsevier Ltd. All rights reserved.
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| 5. |
- Bahnsen, Alejandro, et al.
(författare)
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Cost sensitive credit card fraud detection using bayes minimum risk
- 2013
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Ingår i: Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013. - : IEEE Computer Society. - 9780769551449 ; , s. 333-338
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Konferensbidrag (refereegranskat)abstract
- Credit card fraud is a growing problem that affects card holders around the world. Fraud detection has been an interesting topic in machine learning. Nevertheless, current state of the art credit card fraud detection algorithms miss to include the real costs of credit card fraud as a measure to evaluate algorithms. In this paper a new comparison measure that realistically represents the monetary gains and losses due to fraud detection is proposed. Moreover, using the proposed cost measure a cost sensitive method based on Bayes minimum risk is presented. This method is compared with state of the art algorithms and shows improvements up to 23% measured by cost. The results of this paper are based on real life transactional data provided by a large European card processing company.
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| 6. |
- Demisse, Girum G., et al.
(författare)
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Deformation-Based 3D Facial Expression Representation
- 2018
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Ingår i: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 14:1s, s. 17-1
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Tidskriftsartikel (refereegranskat)abstract
- We propose a deformation-based representation for analyzing expressions fromthree-dimensional (3D) faces. A point cloud of a 3D face is decomposed into an ordered deformable set of curves that start from a fixed point. Subsequently, a mapping function is defined to identify the set of curves with an element of a high-dimensional matrix Lie group, specifically the direct product of SE(3). Representing 3D faces as an element of a high-dimensional Lie group has two main advantages. First, using the group structure, facial expressions can be decoupled from a neutral face. Second, an underlying non-linear facial expression manifold can be captured with the Lie group and mapped to a linear space, Lie algebra of the group. This opens up the possibility of classifying facial expressions with linear models without compromising the underlying manifold. Alternatively, linear combinations of linearised facial expressions can be mapped back from the Lie algebra to the Lie group. The approach is tested on the Binghamton University 3D Facial Expression (BU-3DFE) and the Bosphorus datasets. The results show that the proposed approach performed comparably, on the BU-3DFE dataset, without using features or extensive landmark points.
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| 7. |
- Garcia, Frederic, et al.
(författare)
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A new 1-D colour model and its application to image filtering
- 2011
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Ingår i: ISPA 2011 - 7th International Symposium on Image and Signal Processing and Analysis. ; , s. 134-138
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a new 1-D model to encodecoloured images for an efficient subsequent processing. Thisrepresentation is equivalent to, but more compact than, the 3-DHCL conical representation. It consists in gathering all the hue,chroma and luminance information in one component, namely,the cumulative spiral angle, where the spirals in question aredefined as a sampling of the solid HCL cone. We use theproposed model for joint bilateral upsampling of low-resolutiondepth maps. The results show that, in addition to preserving theperceptual properties of the HCL colour representation, usingthe proposed model leads to a solution that is more accuratethan when using grayscale images.
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| 8. |
- Garcia, Frederic, et al.
(författare)
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A new multi-lateral filter for real-time depth enhancement
- 2011
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Ingår i: 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011. - : IEEE. - 9781457708459 ; , s. 42-47
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Konferensbidrag (refereegranskat)abstract
- We present an adaptive multi-lateral filter for real-time low-resolution depth map enhancement. Despite the great advantages of Time-of-Flight cameras in 3-D sensing, there are two main drawbacks that restricts their use in a wide range of applications; namely, their fairly low spatial resolution, compared to other 3-D sensing systems, and the high noise level within the depth measurements. We therefore propose a new data fusion method based upon a bilateral filter. The proposed filter is an extension the pixel weighted average strategy for depth sensor data fusion. It includes a new factor that allows to adaptively consider 2-D data or 3-D data as guidance information. Consequently, unwanted artefacts such as texture copying get almost entirely eliminated, outperforming alternative depth enhancement filters. In addition, our algorithm can be effectively and efficiently implemented for real-time applications.
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| 9. |
- Garcia, Frederic, et al.
(författare)
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Real-time hybrid ToF multi-camera rig fusion system for depth map enhancement
- 2011
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Ingår i: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- We present a full real-time implementation of a multilateral filtering system for depth sensor data fusion with 2-D data. For such a system to perform in real-time, it is necessary to have a real-time implementation of the filter, but also a real-time alignment of the data to be fused. To achieve an automatic data mapping, we express disparity as a function of the distance between the scene and the cameras, and simplify the matching procedure to a simple indexation procedure. Our experiments show that this implementation ensures the fusion of 3-D data and 2-D data in real-time and with high accuracy.
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| 10. |
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