This paper presents an objective structural distortion measure which reflects the visual similarity between 3D meshes and thus can be used for quality assessment. The proposed tool is not linked to any specific application and thus can be used to evaluate any kinds of 3D mesh processing algorithms (simplification, compression, watermarking etc.). This measure follows the concept of structural similarity recently introduced for 2D image quality assessment by Wang et al. 1 and is based on curvature analysis (mean, standard deviation, covariance) on local windows of the meshes. Evaluation and comparison with geometric metrics are done through a subjective experiment based on human evaluation of a set of distorted objects. A quantitative perceptual metric is also derived from the proposed structural distortion measure, for the specific case of watermarking quality assessment, and is compared with recent state of the art algorithms. Both visual and quantitative results demonstrate the robustness of our approach and its strong correlation with subjective ratings.
Abstract-This paper addresses the problem of assessing distortions produced by watermarking 3D meshes. In particular, a new methodology for subjective evaluation of the quality of 3D objects is proposed and implemented. Two objective metrics derived from measures of surface roughness are then proposed and their efficiency to predict perceptual impact of 3D watermarking are assessed and compared with the state of the art. Results obtained show good correlations between the proposed objective metrics and subjective assessments by human observers.
In this paper, we propose an automatic method for the objective evaluation of segmentation results. The method is based on computing the deviation of the segmentation results from a reference segmentation. The discrepancy between two results is weighted based on spatial and temporal contextual information, by taking into account the way humans perceive visual information. The metric is useful for applications where the final judge of the quality is a human observer or the results of segmentation are otherwise processed in a human-like fashion. The proposed evaluation has been applied both to automatically provide a ranking among different segmentation algorithms and to optimally set the parameters of a given algorithm.
In this paper an objective metric to measure the perceptual quality of watermarked 3D meshes is presented. The metric, which is based on a black-box approach, relies on the measurement of the roughness of 3D meshes before and after the insertion of the watermark. To calibrate the metric and to validate it, a set of psychovisual experiments has been carried out. Due to the lack of prior work in this field, a new methodology for the subjective evaluation of the quality of watermarked 3D objects is introduced. The validity of the proposed metric has been tested against a number of different 3D watermarking algorithms, showing an excellent match with the subjective evaluation of the quality stemming from the pshycovisual experiments.
This paper describes ongoing work on creating a benchmarking and validation dataset for biological image segmentation. While the primary target is biological images, we believe that the dataset would be of help to researchers working in image segmentation and tracking in general. The motivation for creating this resource comes from the observation that while there are a large number of effective segmentation methods available in the research literature, it is difficult for the application scientists to make an informed choice as to what methods would work for her particular problem. No one single tool exists that is effective on a diverse set of application contexts and different methods have their own strengths and limitations. We describe below three different classes of data, ranging in scale from subcellular to cellular to tissue level images, each of which pose their own set of challenges to image analysis. Of particular value to the image processing researchers is that the data comes with associated ground truth information that can be used to evaluate the effectiveness of different methods. The analysis and evaluation are also integrated into a database framework that is available online at
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