References of "Mirbach, Bruno"
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See detailFull 3D Reconstruction of Non-Rigidly Deforming Objects
Afzal, Hassan; Aouada, Djamila UL; Mirbach, Bruno et al

in ACM Transactions on Multimedia Computing, Communications, & Applications (2018)

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See detailReal-Time Enhancement of Dynamic Depth Videos with Non-Rigid Deformations
Al Ismaeil, Kassem; Aouada, Djamila UL; Solignac, Thomas et al

in IEEE Transactions on Pattern Analysis & Machine Intelligence (2016), 39(10), 2045-2059

We propose a novel approach for enhancing depth videos containing non-rigidly deforming objects. Depth sensors are capable of capturing depth maps in real-time but suffer from high noise levels and low ... [more ▼]

We propose a novel approach for enhancing depth videos containing non-rigidly deforming objects. Depth sensors are capable of capturing depth maps in real-time but suffer from high noise levels and low spatial resolutions. While solutions for reconstructing 3D details in static scenes, or scenes with rigid global motions have been recently proposed, handling unconstrained non-rigid deformations in relative complex scenes remains a challenge. Our solution consists in a recursive dynamic multi-frame superresolution algorithm where the relative local 3D motions between consecutive frames are directly accounted for. We rely on the assumption that these 3D motions can be decoupled into lateral motions and radial displacements. This allows to perform a simple local per-pixel tracking where both depth measurements and deformations are dynamically optimized. The geometric smoothness is subsequently added using a multi-level L1 minimization with a bilateral total variation regularization. The performance of this method is thoroughly evaluated on both real and synthetic data. As compared to alternative approaches, the results show a clear improvement in reconstruction accuracy and in robustness to noise, to relative large non-rigid deformations, and to topological changes. Moreover, the proposed approach, implemented on a CPU, is shown to be computationally efficient and working in real-time. [less ▲]

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See detailEnhancement of Dynamic Depth Scenes by Upsampling for Precise Super-Resolution (UP-SR)
Al Ismaeil, Kassem; Aouada, Djamila UL; Mirbach, Bruno et al

in Computer Vision and Image Understanding (2016)

Multi-frame super-resolution is the process of recovering a high resolution image or video from a set of captured low resolution images. Super-resolution approaches have been largely explored in 2-D ... [more ▼]

Multi-frame super-resolution is the process of recovering a high resolution image or video from a set of captured low resolution images. Super-resolution approaches have been largely explored in 2-D imaging. However, their extension to depth videos is not straightforward due to the textureless nature of depth data, and to their high frequency contents coupled with fast motion artifacts. Recently, few attempts have been introduced where only the super-resolution of static depth scenes has been addressed. In this work, we propose to enhance the resolution of dynamic depth videos with non-rigidly moving objects. The proposed approach is based on a new data model that uses densely upsampled, and cumulatively registered versions of the observed low resolution depth frames. We show the impact of upsampling in increasing the sub-pixel accuracy and reducing the rounding error of the motion vectors. Furthermore, with the proposed cumulative motion estimation, a high registration accuracy is achieved between non-successive upsampled frames with relative large motions. A statistical performance analysis is derived in terms of mean square error explaining the effect of the number of observed frames and the effect of the super-resolution factor at a given noise level. We evaluate the accuracy of the proposed algorithm theoretically and experimentally as function of the SR factor, and the level of contaminations with noise. Experimental results on both real and synthetic data show the effectiveness of the proposed algorithm on dynamic depth videos as compared to state-of-art methods. [less ▲]

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See detailUnified Multi-Lateral Filter for Real-Time Depth Map Enhancement
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Mirbach, Bruno et al

in Image & Vision Computing (2015), 41

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See detailReal-Time Non-Rigid Multi-Frame Depth Video Super-Resolution
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Solignac, Thomas et al

in IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'15), (Best paper award) (2015, June 12)

This paper proposes to enhance low resolution dynamic depth videos containing freely non–rigidly moving objects with a new dynamic multi–frame super–resolution algorithm. Existent methods are either ... [more ▼]

This paper proposes to enhance low resolution dynamic depth videos containing freely non–rigidly moving objects with a new dynamic multi–frame super–resolution algorithm. Existent methods are either limited to rigid objects, or restricted to global lateral motions discarding radial displacements. We address these shortcomings by accounting for non–rigid displacements in 3D. In addition to 2D optical flow, we estimate the depth displacement, and simultaneously correct the depth measurement by Kalman filtering. This concept is incorporated efficiently in a multi–frame super–resolution framework. It is formulated in a recursive manner that ensures an efficient deployment in real–time. Results show the overall improved performance of the proposed method as compared to alternative approaches, and specifically in handling relatively large 3D motions. Test examples range from a full moving human body to a highly dynamic facial video with varying expressions. [less ▲]

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See detailView-Independent Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects
Afzal, Hassan UL; Aouada, Djamila UL; Destelle, Francois et al

in 16th International Conference on Computer Analysis of Images and Patterns (2015)

In this paper, we target enhanced 3D reconstruction of non-rigidly deforming objects based on a view-independent surface representation with an automated recursive filtering scheme. This work improves ... [more ▼]

In this paper, we target enhanced 3D reconstruction of non-rigidly deforming objects based on a view-independent surface representation with an automated recursive filtering scheme. This work improves upon the KinectDeform algorithm which we recently proposed. KinectDeform uses an implicit viewdependent volumetric truncated signed distance function (TSDF) based surface representation. The view-dependence makes its pipeline complex by requiring surface prediction and extraction steps based on camera’s field of view. This paper proposes to use an explicit projection-based Moving Least Squares (MLS) surface representation from point-sets. Moreover, the empirical weighted filtering scheme in KinectDeform is replaced by an automated fusion scheme based on a Kalman filter. We analyze the performance of the proposed algorithm both qualitatively and quantitatively and show that it is able to produce enhanced and feature preserving 3D reconstructions. [less ▲]

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See detailKinectDeform: Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects
Afzal, Hassan UL; Al Ismaeil, Kassem UL; Aouada, Djamila UL et al

in Second International Conference on 3D Vision (2014)

In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of scenes containing non-rigidly deforming objects. It provides an innovation to the existing class of ... [more ▼]

In this work we propose KinectDeform, an algorithm which targets enhanced 3D reconstruction of scenes containing non-rigidly deforming objects. It provides an innovation to the existing class of algorithms which either target scenes with rigid objects only or allow for very limited non-rigid deformations or use pre-computed templates to track them. KinectDeform combines a fast non-rigid scene tracking algorithm based on octree data representation and hierarchical voxel associations with a recursive data filtering mechanism. We analyze its performance on both real and simulated data and show improved results in terms of smoothness and feature preserving 3D reconstructions with reduced noise. [less ▲]

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See detailRGB-D Multi-View System Calibration for Full 3D Scene Reconstruction
Afzal, Hassan UL; Aouada, Djamila UL; Fofi, David et al

in 22nd International Conference on Pattern Recognition (ICPR'14) (2014)

One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We ... [more ▼]

One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially. [less ▲]

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See detailRange Image Pixel Matching Method
Garcia Becerro, Frederic UL; Mirbach, Bruno

Patent (2013)

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See detailDynamic Super Resolution of Depth Sequences with Non-Rigid Motions
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Mirbach, Bruno et al

in 20th International Conference on Image Processing (2013, September)

We enhance the resolution of depth videos acquired with low resolution time-of-flight cameras. To that end, we propose a new dedicated dynamic super-resolution that is capable to accurately super-resolve a ... [more ▼]

We enhance the resolution of depth videos acquired with low resolution time-of-flight cameras. To that end, we propose a new dedicated dynamic super-resolution that is capable to accurately super-resolve a depth sequence containing one or multiple moving objects without strong constraints on their shape or motion, thus clearly outperforming any existing super-resolution techniques that perform poorly on depth data and are either restricted to global motions or not precise because of an implicit estimation of motion. Our proposed approach is based on a new data model that leads to a robust registration of all depth frames after a dense upsampling. The texture-less nature of depth images allows to robustly handle sequences with multiple moving objects as confirmed by our experiments. [less ▲]

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See detailReal-time depth enhancement by fusion for RGB-D cameras
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Solignac, Thomas et al

in IET Computer Vision (2013), 7(5), 335345

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See detailMutli-Frame Super-Resolution by Enhanced Shift & Add
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Mirbach, Bruno et al

in 8th International Symposium on Image and Signal Processing and Analysis (2013)

A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more ... [more ▼]

A critical step in multi-frame super-resolution is the registration of frames based on their motion. We improve the performance of current state-of-the-art super-resolution techniques by proposing a more robust and accurate registration as early as in the initialization stage of the high resolution estimate. Indeed, we solve the limitations on scale and motion inherent to the classical Shift & Add approach by upsampling the low resolution frames up to the super-resolution factor prior to estimating motion or to median filtering. This is followed by an appropriate selective optimization, leading to an enhanced Shift & Add. Quantitative and qualitative evaluations have been conducted at two levels; the initial estimation and the final optimized super-resolution. Results show that the proposed algorithm outperforms existing state-of-art methods. [less ▲]

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See detailDepth Super-Resolution by Enhanced Shift and Add
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Mirbach, Bruno et al

in Computer Analysis of Images and Patterns, 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part II (2013)

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See detailBilateral Filter Evaluation Based on Exponential Kernels
Al Ismaeil, Kassem UL; Aouada, Djamila UL; Mirbach, Bruno et al

in Pattern Recognition (ICPR), 2012 21st International Conference on (2012)

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 ... [more ▼]

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. [less ▲]

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See detailDepth Enhancement by Fusion for Passive and Active Sensing
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Abdella, Hashim Kemal UL et al

in Computer Vision – ECCV 2012. Workshops and Demonstrations (2012)

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See detailSpatio-Temporal ToF Data Enhancement by Fusion
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Mirbach, Bruno et al

in 19th IEEE International Conference on Image Processing (2012)

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See detailReal-Time Distance-Dependent Mapping for a Hybrid ToF Multi-Camera Rig
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Mirbach, Bruno et al

in IEEE Journal of Selected Topics in Signal Processing (2012), 6(5), 1-12

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See detail3D Time-Of-Flight Camera System and Position/Orientation Calibration Method Therefor
Garcia Becerro, Frederic UL; Grandidier, Frederic; Mirbach, Bruno et al

Patent (2011)

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See detailSpiral Colour Model: Reduction from 3-D to 2-D
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Mirbach, Bruno et al

in International Conference on Acoustics, Speech and Signal Processing (2011)

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See detailReal-Time Hybrid ToF Multi-Camera Rig Fusion System for Depth Map Enhancement
Garcia Becerro, Frederic UL; Aouada, Djamila UL; Mirbach, Bruno et al

in 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2011)

Detailed reference viewed: 104 (2 UL)