![]() ![]() The proposed system is limited by its cost and portability. Solving the inverse kinematics problem of the system and collision avoidance are key to trajectory planning while executing the acquisition. Moreover, the system, when combined with the Next Best Light Position, can be used as a standalone unit to perform fully automated RTI acquisition adjustable to the complexity of the object’s surface geometry. LightBot accepts the standard Light Positions (.lp) file containing a predefined set of light directions and executes the acquisition by moving the light source oriented in the given directions. With the autonomous translation of the surface between acquisition sequences, it is, according to our knowledge, the first approach towards the automation of the RTI acquisition process for medium and large surfaces that cannot be acquired in the conventional dome systems. LightBot, the system we propose, is an efficient, surface-adaptive RTI acquisition system designed and built for developing new methods in RTI. In Section 4, we draw conclusions on the proposed system, discussing its applications and the plan for future systems. In Section 3, we demonstrate the capability and application of LightBot, showing the implementation and results of our methods on a few cultural heritage surfaces. We present the mechanical aspects of our system in Section 2. ![]() The proposed system addresses this challenge of performing RTI on large-scale surfaces. The current state-of-the-art acquisition systems are unsuitable for large-scale surface measurement and stitching. ![]() Moreover, automation can find ground when there is a need to make repetitive acquisitions, such as in documenting a series of coin collections or for monitoring the condition of an object over time. This is an important feature, particularly for medium- and large-sized cultural heritage objects such as paintings, manuscripts, etc., having complex surfaces. ![]() This coupling can enable a lot of possibilities since it allows the creation of any type of virtual dome. In our case, the camera remains stationary and the robot arm is used to move the light source. for acquiring BRDF data, where the robot arm is used to move the camera and a turntable is used to manipulate the object being scanned. Another robot-based system was designed and built by Santos et al. present a method using a robot arm for RTI acquisition, but the details of the system, its capabilities and limitations are not presented. LightBot is the first attempt to use both a robot arm to control the light position and an XY stage to control the surface position to enable several aspects of RTI, such as data stitching, adaptive acquisitions, etc. ( a) Free-form highlight-RTI (a acquisition performed by our group), ( b) Dome system, ( c) Proposed system-LightBot. In Figure 2, a typical free-form hightlight-RTI setup, a dome-based setup and our proposed system are shown for illustration. On the other hand, dome-based systems provide the necessary repeatability but have limitations on the object size as well as a limited angular area for light positioning and portability. This allows multi-scale acquisitions however, repeatability and reproducibility are compromised due to the difficulty of retrieving the same light positions. The free-form RTI systems provide more freedom in the setup since the acquisitions are usually performed with portable instrumentation using a handheld light source and a camera attached to a tripod with adjustable position. The multi-light acquisition systems can be broadly categorized into two types: free-form highlight-RTI or dome-based. These modelling plots are reprinted with permission from Pitard et al. An example of the per pixel reflectance modeling using is shown here ( a) PTM, ( b) HSH and ( c) DMD. Reflectance transformation imaging technique. Figure 1 illustrates the RTI process where images of a surface captured each with discrete lighting conditions are fitted to a mathematical model representing the reflectance of the surface. We focus on RTI systems as they have proven to provide an accurate description of important parameters related to the surface appearance and geometry and thus have found application in the study and analysis of cultural heritage (CH) surfaces. Photometric stereo has the goal of reconstructing a 3D view of the object, whereas RTI aims for interactive relighting of the surface. We can cite, for instance, photometric stereo and reflectance transformation imaging (RTI), consisting of imaging an object from a fixed camera view while varying the light direction for each image captured. Multi-light image collections regroup a series of techniques that allow the acquisition of a collection of images where only the lighting conditions vary (its spatial position or spectral content). ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |