Ham M. Rara

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Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we propose a novel 3D shape based method to segment VBs in clinical computed tomography (CT) images without any user intervention. The proposed method depends on both image appearance and shape information. 3D shape(More)
Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we present a novel and fast 3D segmentation framework of VBs in clinical CT images using the graph cuts method. The Matched filter is employed to detect the VB region automatically. In the graph cuts method, a VB(More)
We describe a framework for face recognition at a distance based on sparse-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted on pan-tilt units with adjustable baseline. We first detect the facial region and extract its landmark points, which are used to initialize an AAM mesh fitting algorithm. The(More)
Face and eye detection algorithms are deployed in a wide variety of applications. Unfortunately, there has been no quantitative comparison of how these detectors perform un­ der difficult circumstances. We created a dataset of low light and long distance images which possess some of the problems encountered by face and eye detectors solving real world(More)
We present a new statistical shape-from-shading framework for images of unknown illumination. The object (e.g., face) to be reconstructed is described by a parametric model. To deal with arbitrary illumination, the framework makes use of recent results that general lighting can be expressed using low-order spherical harmonics for convex Lambertian objects.(More)
This paper introduces a framework for long-distance face recognition using both dense-and sparse-stereo reconstruction. Two methods to determine correspondences of the stereo pair are used in this paper: (a) dense global stereo matching using maximum-a-posteriori Markov Random Fields (MAP-MRF) algorithms and (b) Active Appearance Model (AAM) fitting of both(More)
This paper proposes a model-based approach for 3D fa­ cial shape recovery using a small set of feature points from an input image of unknown pose and illumination. Previous model-based approaches usually require both texture (shad­ ing) and shape information from the input image in order to perform 3D facial shape recovery. However, the methods discussed(More)
We discuss a statistical shape-from-shading framework for images of general and unknown illumination. To overcome arbitrary illumination, the framework makes use of the fact that general lighting can be expressed using low-order spherical harmonics for convex Lambertian objects. We cast the classical shape-from-shading equation as a Partial Least Squares(More)
This paper introduces a framework for long-distance face recognition using dense and sparse stereo reconstruction , with texture of the facial region. Two methods to determine correspondences of the stereo pair are used in this paper: (a) dense global stereo-matching using maximum-a-posteriori Markov Random Fields (MAP-MRF) algorithms and (b) Active(More)
The visual appearance of real-world surfaces is the net result of surface reflectance characteristics when exposed to illumination. Appearance models can be constructed using phenomenological models which capture surface appearance through mathematical modeling of the reflection process. This yields an integral equation, known as reflectance equation,(More)