This paper presents a review of the most relevant current techniques that deal with hole-filling in 3D models. Contrary to earlier reports, which approach mesh repairing in a sparse and global manner, the objective of this review is twofold. First, a specific and comprehensive review of hole-filling techniques (as a relevant part in the field of mesh repairing) is carried out. We present a brief summary of each technique with attention paid to its algorithmic essence, main contributions and limitations. Second, a solid comparison between 34 methods is established. To do this, we define 19 possible meaningful features and properties that can be found in a generic hole-filling process. Then, we use these features to assess the virtues and deficiencies of the method and to build comparative tables. The purpose of this review is to make a comparative hole-filling state-of-the-art available to researchers, showing pros and cons in a common framework.

People with disabilities encounter numerous barriers when dealing with the simplest and most usual things in their daily lives. This is even more remarkable when they are faced with archaeological heritage buildings or environments. People with reduced mobility come too often upon architectural barriers that stop them from enjoying their visits to sites and monuments. This paper introduces a virtual reality (VR) experience developed to provide people in wheelchairs with the most realistic sensations while virtually touring some archaeological sites. To this end, the remote sensing of the site enables the production of a realistic 3D model leading to the creation of a virtual world that the user will explore. This VR application has been developed to traverse one of the most important monumental buildings in Spanish Protohistory, the site of Cancho Roano (Zalamea de la Serena, Spain).

This work analyzes a new method for object recognition in complex scenes combining vision-based techniques applied to the 3-D data obtained using range sensors and object identification coming from radio frequency tags (radio frequency identification (RFID) technology). Three-dimensional vision-based algorithms for object recognition have many restrictions in practical applications, i.e., uncertainty, incapability for real-time tasks, etc., but they work well for pose determination once the object is recognized. On the other hand, RFID technology allows us to detect the presence of specific objects in a scene, but it cannot provide their localization, at least not with the accuracy required in applications such as ours. In this paper, we present a new and powerful recognition method obtained by fusing both techniques. The phases of the method are described, and abundant experimentation results are included. An in-depth performance analysis has been carried out to demonstrate the recognition improvements achieved by the algorithm when RFID assistance is considered. It helps to confirm the robustness of this fusion approach and prove its effectiveness. A final discussion is included, concerning what should be the most adequate size of the object database for optimal algorithm exploitation.

This paper proposes a solution based on computer vision to detect solar panels in images. It is based on the definition of a feature vector that characterizes portions of images that can be acquired with a standard camera and with no lighting restrictions. The proposal has been applied to a set of images taken in an operating photovoltaic plant and the results obtained demonstrate its validity and robustness. These results are meant to be used in later stages of a procedure for the optimization of energy efficiency.