This research aims to obtain more insight into the perception of fabric drape and how this relates to virtual fabric drape created based on objective fabric properties using commercial software applications, as well as the suitability of the currently used objective fabric measurement technologies for this purpose, and subsequently how this insight can contribute to comprehensible assessment of fabrics in a virtual or digital environment.The fashion and clothing industry can speed up work processes, increase accuracy and reduce material consumption by implementing 3D virtual technology in fit, design and sales. Although the interest in 3D technology increases, the implementation on a large scale is slow. Key for a successful implementation is an accurate, reliable and seamless interaction between virtual humans, 2D patterns and virtual fabrics.Subjective and objective data were acquired. With established instruments the measurements were taken from a range of 12 selected fabrics; the drape coefficient with the Cusick drape tester, the fabrics physical and mechanical properties with the Kawabata Evaluation System for Fabrics (KES) and Fabric Assurance by Simple Testing (FAST). The data of KES and FAST were used to simulate the virtual cloth, from which a virtual drape coefficient was derived.Drape images were created from two different viewpoints and videos from one view point, both on two different supports. The input of an expert textile panel to define the fabric drape based on these drape images was used to categorise the fabric drape and to retrieve identifying key-words. An expert user panel validated the drape categories and key-words. They also defined the stiffness and amount of drape, as well as the drape similarity of both the physical and virtual cloth. Additionally, they gave their preference for the support and view to obtain information about the fabric drape.The relationships between drape coefficient and physical and mechanical properties were statistically investigated, as well as the relationships between the physical and virtual fabric drape coefficient. These objective measurements were correlated with the subjective data. For the correlations Pearson's correlation coefficient was used and the significance values were obtained.The agreement of the user panel with the drape categories defined and evaluated by the textile panel was high. Further, the agreement of the user panel was above 78% for the majority of the identifying key words. The information obtained from the abstracted drape profile was valuable and the sphere support and the 3D videos of the drape were most preferred.High correlations were found between the drape coefficients, of the real and virtual drape, and of the subjective assessment of stiffness and the amount of drape. Positive significant correlations were found between the drape coefficients and bending and shear properties measured with KES and FAST, as well as with the fabrics' weights. The panels were able to classify fabrics in categories based on the way they drape and the identifying key-words are useful to distinguish between fabrics with a similar drape. The KES and FAST data simulated in a particle mesh with commercial software represent the drape of a fabric in a sufficient way. Moreover, different perspectives on the drape contributed to more insight into the drape of the fabric.