Khadija Arhid

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Recently, the 3D mesh segmentation is considered as an important stage in many applications in 3D shape analysis. In fact, extensive research has been performed to offer multiple approaches and algorithms for 3D mesh segmentation. Nevertheless, it is relatively hard to assess which algorithm produces more accurate segmentation quality than the other.(More)
It is widely recognized that the segmentation of 3D objects is one of the most important disciplines in computer vision. In the last few years, developments of 3D segmentation techniques are in continual expansion. However, little work has been directed toward the evaluation of 3D mesh segmentation methods and consequently there is still no satisfactory(More)
In the last few years, the request for a content-based 3D object retrieval system has become a significant issue. At this point, the principal challenge is the mapping of the 3D objects into compact representations referred to as descriptors, which serve as search keys over the retrieval process. In this paper, a new approach will be proposed for 3D objects(More)
3D segmentation methods and their evaluation are important problems in computer graphics. Many 3D segmentation techniques are available in the literature, how to efficiently evaluate these methods is an important issue. In this paper we propose a new objective evaluation metric suitable for the evaluation of 3D segmentation methods, based on the Dice(More)
Despite several decades of research into 3D segmentation techniques and a diversity of methods and approaches proposed in the literature, comparing and evaluating the quality of this segmentation method is still a challenging task to achieve. In this paper, an objective evaluation metric suitable for evaluation of 3D segmentation quality and based on the(More)
3D segmentation and its performance evaluation play a crucial role in computer vision. Due to its importance, much effort has been consecrated to the segmentation process in the last decades. Consequently, the development of reasonable criteria for evaluating and comparing the performance of segmentation algorithms has become a major challenge in the area.(More)
Segmentation of 3D models plays a major role in many computer vision applications. Over the last few decades, extensive research has been done to propose many different segmentation algorithms. However, comparing the segmentation quality of multiple algorithms still a difficult task. Recently, many works have been proposed to solve this problem by comparing(More)
Decomposing a 3D mesh into significant regions is considered as a fundamental process in computer graphics, since several algorithms use the segmentation results as an initial step, such as, skeleton extraction, shape retrieval, shape correspondence, and compression. In this work, we present a new segmentation algorithm using spectral clustering where the(More)
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