Recently, several works have been proposed in the literature to take advantage of the diffusion of smartphones to improve people experience during museum visits. The rationale is that of substituting traditional written/audio guides with interactive electronic guides usable on a mobile phone. Augmented reality systems are usually considered to make the use of such electronic guides more effective for the user. <p> </p>The main goal of such augmented reality system (i.e. providing the user with the information of his/her interest) is usually achieved by properly executing the following three tasks: recognizing the object of interest to the user, retrieving the most relevant information about it, properly presenting the retrieved information. <p> </p>This paper focuses on the first task: we consider the problem of painting recognition by means of measure- ments provided by a smartphone. We assume that the user acquires one image of the painting of interest with the standard camera of the device. This image is compared with a set of reference images of the museum objects in order to recognize the object of interest to the user. Since comparing images taken in different conditions can lead to unsatisfactory recognition results, the acquired image is typically properly transformed in order to improve the results of the recognition system: first, the system estimates the homography between properly matched features in the two images. Then, the user image is transformed accordingly to the estimated homography. Finally, it is compared with the reference one. <p> </p>This work proposes a novel method to exploit inertial measurement unit (IMU) measurements to improve the system performance, in particular in terms of computational load reduction: IMU measurements are exploited to reduce both the computational burden required to estimate the transformation to be applied to the user image, and the number of reference images to be compared with it.
In the last decade, the demand of 3D models for objects documentation and visualization is drastically increased. 3D modeling of close-range objects is required in different applications, like cultural heritage, industry, animation or medicine. While Photogrammetry is a well proved technique for 3D reconstruction of real objects, featuring important properties like accurate sensor calibration, use of both analog or digital imageries, low cost and high portable system, laser scanning technology is becoming a very promising alternative for surveying and modeling applications. Tipically, laser scanners allow for fast acquisition of huge amount of 3D data which can be often combined with colour hi-res digital images. As a result, real objects can be represented with a higher level of detail together with a good metric accuracy. Among several works so far presented about laser scanning for cultural heritage survey, some modeling and accuracy related issues have been not yet solved and discussed in details. In this contribution we report about two case studies realized with photogrammetry and laser scanner and we provide some advices and suggestions about the more suitable 3D modeling method for a given object, taking into account its size and shape complexity, the required accuracy and the target application.
The arising interest towards 3D modeling of both single objects and whole environments is strictly related with the availability of more and more powerful computing and surveying devices. A new set of issues has to be addressed in the 3D modeling of real objects. A lot of data are needed about the object surface or volume, which have then to be aggregated, regardless the data format and the acquisition device used, in order to get the final model. Actually, the data registration requires an approximate estimate of the alignement between acquired data.This approach is often time-consuming, increases the final cost of the 3D model and represents the major limit to the wide spreading of real object models. Taking into account this drawback, a fully automatic range data registration system has been developed. This system is able to execute all the steps needed for 3D modeling of real objects in automatic way or at least minimizing as more as possible the human intervention, without any other information but the range data only. In this paper an overview of the whole registration system is presented, focusing on the integration between the two main blocks. In the first one, overlapping areas between range image pairs are detected by mean of spin-images and an initial approximate alignement between image pairs is computed. Then, in the second block, a refinement of this estimate is performed by use of a cascade of two registration algorithms: the Frequency Domain and the ICP. Some interesting applications of proposed strategy for 3D modeling of cultural heritage objects will be also reported.
Phase correlation is a very robust technique to estimate image translations, but it works only for monochromatic images. If the input image is a color image, it must be first converted to monochrome, wasting part of the input information. In this work we extend the phase correlation algorithm to the case of multi-component images such as RGB and multi-spectral images.