0000000000934133

AUTHOR

Albert Dipanda

Multiple Structured Light-Based Depth Sensors for Human Motion Analysis: A Review

Human motion analysis is an increasingly important active research domain with various applications in surveillance, human-machine interaction and human posture analysis. The recent developments in depth sensor technology, especially with the release of the Kinect device, have attracted significant attention to the question of how to take advantage of this technology in order to achieve accurate motion tracking and action detection in marker-less approaches. In this paper, we review the benefits and limitations deriving from the adoption of structured light-based depth sensors in human motion analysis applications. Surveying the relevant literature, we have identified in calibration, interf…

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Ninth International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2013, Kyoto, Japan, December 2-5, 2013

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SAR Image Classification Combining Structural and Statistical Methods

The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…

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Real-time signal processing in embedded systems

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Three-dimensional rigid motion estimation using genetic algorithms from an image sequence in an active stereo vision system

This paper proposes a method for estimating the three-dimensional (3D) rigid motion parameters from an image sequence of a moving object. The 3D surface measurement is achieved using an active stereovision system composed of a camera and a light projector, which illuminates the objects to be analyzed by a pyramid-shaped laser beam. By associating the laser rays with the spots in the two-dimensional image, the 3D points corresponding to these spots are reconstructed. Each image of the sequence provides a set of 3D points, which is modeled by a B-spline surface. Therefore, estimating the 3D motion between two images of the sequence boils down to matching two B-spline surfaces. We consider the…

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Signal Processing for Image Enhancement and Multimedia Processing

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Message from SIT Track Chairs

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Using Fourier local magnitude in adaptive smoothness constraints in motion estimation

Like many problems in image analysis, motion estimation is an ill-posed one, since the available data do not always sufficiently constrain the solution. It is therefore necessary to regularize the solution by imposing a smoothness constraint. One of the main difficulties while estimating motion is to preserve the discontinuities of the motion field. In this paper, we address this problem by integrating the motion magnitude information obtained by the Fourier analysis into the smoothness constraint, resulting in an adaptive smoothness. We describe how to achieve this with two different motion estimation approaches: the Horn and Schunck method and the Markov Random Field (MRF) modeling. The t…

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Apport du variogramme dans la classification d'images satellitaires radar RSO,

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Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

L'analyse prédictive permet d'estimer les tendances des évènements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes prédictions. Cependant, pour chaque type de problème donné, il est nécessaire de choisir l'architecture optimale. Dans cet article, les modèles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqués à une série temporelle d'images radar sentinel-1, le but étant de prédire la prochaine occurrence dans une séquence. Les résultats expérimentaux évalués à l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarité SSIM, montrent que chacune des trois architectures peut produire de bons résultats en fon…

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A Parallel Approach for Statistical Texture Parameter Calculation

This chapter focusses on the development of a new image processing technique for the processing of large and complex images, especially SAR images. We propose here a new and effective approach that outperforms the existing methods for the calculation of high order textural parameters. With a single processor, this approach is about \(256^{n-1}\) times faster than the co-occurrence matrix approach considered as classical, where \(n\) is the order of the textural parameter for a 256-gray scales image. In a parallel environment made of N processor, this performance can almost be multiply by the factor N. Our approach is based on a new modeling of textural parameters of a generic order \(n>1\) …

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User profile matching in social networks

International audience; Inter-social networks operations and functionalities are required in several scenarios (data integration, data enrichment, information retrieval, etc.). To achieve this, matching user profiles is required. Current methods are so restrictive and do not consider all the related problems. Particularly, they assume that two profiles describe the same physical person only if the values of their Inverse Functional Property or IFP (e.g. the email address, homepage, etc.) are the same. However, the observed trend in social networks is not fully compatible with this assumption since users tend to create more than one social network account (for personal use, for work, etc.) w…

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Toward a real-time tracking of dense point-sampled geometry

4 pages; International audience; In this paper, we address the problem of tracking temporal deformations between two arbitrary densely sampled point-based surfaces. We propose an intuitive and efficient resolution to the point matching problem within two frames of a sequence. The proposed method utilizes two distinct space partition trees, one for each point cloud, which both are defined on a unique discrete space. Our method takes advantage of multi-resolution concerns, voxel adjacency relations, and a specific distance function. Experimental results obtained from both simulated and real reconstructed data sets demonstrate that the proposed method can handle efficiently the tracking proces…

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3-D shape reconstruction in an active stereo vision system using genetic algorithms

Abstract The recovery of 3-D shape information (depth) using stereo vision analysis is one of the major areas in computer vision and has given rise to a great deal of literature in the recent past. The widely known stereo vision methods are the passive stereo vision approaches that use two cameras. Obtaining 3-D information involves the identification of the corresponding 2-D points between left and right images. Most existing methods tackle this matching task from singular points, i.e. finding points in both image planes with more or less the same neighborhood characteristics. One key problem we have to solve is that we are on the first instance unable to know a priori whether a point in t…

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Efficient correspondence problem-solving in 3-D shape reconstruction using a structured light system

This paper deals with 3-D object reconstruction using a structured light system (SLS). The SLS is composed of a camera and a laser projector that illuminates spots on the scene of interest. The basic problem of such a system is the correspondence problem. If the correct correspondence between the imaged spots and the projected laser rays is found, the 3-D coordinates of the physical points associated with these spots can be calculated. We propose a method that automatically provides SLS configurations (i.e., the relative positions of both camera and laser projector with respect to the object to be analyzed) that allow performing an unambiguous and direct correspondence procedure. Experiment…

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SITIS 2012 Foreword

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SIT: Track on Signal Image Technology

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Eighth International Conference on Signal Image Technology and Internet Based Systems, SITIS 2012, Sorrento, Naples, Italy, November 25-29, 2012

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12th International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2016, Naples, Italy, November 28 - December 1, 2016

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Direct 3D Information Determination in an Uncalibrated Stereovision System by Using Evolutionary Algorithms

This paper proposes a 3D panoramic shape reconstruction method based on an uncalibrated stereovision system (USS) composed of five cameras circularly located around the object to be analysed. First, some interesting points are detected from markers placed on the object such that they are visible by two successive cameras of the USS. These points are then matched on both images acquired by a couple of successive cameras. This process is repeated for all the couples of cameras. Second, by using an evolutionary algorithm, the depth values of the different interesting points are calculated. A comparison with a traditional method based on calibrated cameras validates the accuracy of 3D informati…

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Towards a real-time 3D shape reconstruction using a structured light system

This paper deals with 3D shape reconstruction using a structured light system (SLS) which projects a matrix of laser rays onto the scene to be analyzed. The intrinsic problem of such a system is the correspondence problem solving, which in this particular case amounts to matching up the imaged spots and the originating laser rays. In this paper, we propose a method for automatically obtaining configurations of the system (COS) (i.e. the relative positions of the camera, laser projector, and measuring scene) that permit to achieve a direct and unambiguous correspondence. After, we propose a splitting cell algorithm, which efficiently performs a real-time correspondence procedure. Experimenta…

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Tenth International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014, Marrakech, Morocco, November 23-27, 2014

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3D Point Cloud Descriptor for Posture Recognition

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14th International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2018

International audience; The SITIS conference is dedicated to research on the technologies used to represent, share and process information in various forms, ranging from signal, image, and multimedia data to traditional structured data and semi-structured data found in the web.SITIS spans two inter-related research domains that increasingly play a key role in connecting systems across network centric environments to allow distributed computing and information sharing. SITIS 2018 aims to provide a forum for high quality presentations on research activities centered on the following main tracks.The track titled "Signal Image & Vision Technologies" (SIVT) focuses on recent developments in digi…

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Application of Genetic Algorithms to 3-D Shape Reconstruction in an Active Stereo Vision System

In this paper, a new method for reconstructing 3-D shapes is proposed. It is based on an active stereo vision system composed of a camera and a light system which projects a set of structured laser rays on the scence to be analyzed. The depth information is provided by matching the laser rays and the corresponding spots appearing in the image. The matching task is performed by using Genetic Algorithms (GAs). The process converges towards the optimum solution which proves that GAs can effectively be used for this problem. An efficient 3-D reconstruction method is introduced. The experimental results demonstrate that the proposed approach is stable and provides high accuracy 3-D object recons…

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Temporal Denoising of Kinect Depth Data

The release of the Microsoft Kinect has attracted the attention of researchers in a variety of computer science domains. Even though this device is still relatively new, its recent applications have shown some promising results in terms of replacing current conventional methods like the stereo-camera for robotics navigation, multi-camera system for motion detection and laser scanner for 3D reconstruction. While most work around the Kinect is on how to take full advantage of its capabilities, so far only a few studies have been carried out on the limitations of this device and fewer that provide solutions to enhance the precision of its measurements. In this paper, we review and analyse curr…

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Tracking Hands in Interaction with Objects: A Review

Markerless vision-based 3D hand motion tracking is a key and popular component for interaction studies in many domains such as virtual reality and natural human-computer interfaces. While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the environment or the other articulated human body parts. Employing contextual information about the surrounding environment (e.g. the shape, the texture, and the posture of the object in the hand) can remarkably constrain the tracking problem. The goal of this survey is to develop an up-to-date taxonomy of existing vision-based hand tracking m…

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Evolutionary-based 3D reconstruction using an uncalibrated stereovision system: application of building a panoramic object view

In this paper, we propose an original evolutionary-based method for 3D panoramic reconstruction from an uncalibrated stereovision system (USS). The USS is composed of five cameras located on an arc of a circle around the object to be analyzed. The main originality of this work concerns the process of the calculation of the 3D information. Actually, with our method, 3D coordinates are directly obtained without any prior estimation of the fundamental matrix. The method operates in two steps. Firstly, points of interest are detected in pairs of images acquired by two consecutive cameras of the USS are matched. And secondly, using evolutionary algorithms, we jointly compute the transformed matr…

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High Order Textural Classification of Two SAR ERS Images on Mount Cameroon

Abstract Many researchers have demonstrated that textural data increase the precision of a classification when they are combined with level of grey information. However, the calculation of textural parameters of order two is often too long in a computer. The problem is more complex when one must compute higher order textural parameters, which however can considerably improve the precision of a classification. This work is based on statistical methods of order two and three for the calculation of textural parameters [Akono et al., 2003]. In this work, we suggest a new method of calculation of textural parameters, which is more general, not limiting itself only on order two or three, but whic…

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