## 1 Introduction  
In the industrial manufacturing and biomedical industries, there are many situations in which three-dimensional (3D) spatial measurement, tracking and identification of the targets of interest in a volume are required. Among these scenarios, one or all of status information including the dimensions, the locations and the materials are required to be detected due to the working conditions, operation flow, process control, and other requirements. According to the numerous different applications in consumer electronics, car industries, plane industries, or biomedical research and industries, transparent objects must meet different quality requirements with compound measurements of the target of interests. Usually, visual observation or automated machine vision techniques can partially fulfill the abovementioned tasks on the premise of human intervention or complicated and inefficient measurement processes, which obviously cannot meet the actual production requirements in terms of multiple measurands, measuring speed and on-machine measurement. With the continuous advancement of science and technology, various methodologies and techniques have been developed to perform measurements of various measurands, including dimensions [1], spatial locations [2; 3] and materials [4; 5; 6]. Three-dimensional measurement methods, such as light scattering techniques [7], fiber interferometry [8] and optical slope sensors [9], usually measure the surface profile rather than targets of interests in a volume or a free 3D space. Stereovision is an effective way to detect 3D objects, but often requires multiple image sensors, complex calibration process and high requirements of rigidity to keep the baseline. Fringe projection profilometry is another potential method to measure various targets in a volume, but the projected pattern has high vulnerability when facing semi-transparent medium and targets in motion. Moreover, considering the measurements in transparent material or in a volume, optical coherent tomography (OCT) can be used in glass inspection [10]. OCT can obtain clear images and defect depth, but the inevitable scanning makes its detection speed greatly reduced. Autostereoscopic metrology is an emerging technology that was originally developed for the on-machine measurement of micro-structured surfaces [11]. The compact system design can provide fast data acquisition of 3D raw data through the incorporation of a micro lens array (MLA) and high accuracy in three-dimensional (3D) reconstruction due to the reversibility of optical rays in the recording process and reconstruction process of this autostereoscopic measurement method. The autostereoscopic 3D metrology method has very strong advantages in measuring targets in free 3D space, such as in a volume or a transparent material, since it has good extendibility of measuring scale from the macroscopic to the microscopic level and has few limitations of the optical information receiving process since the image sensors can receive reflected or refracted light signals from different targets and medium. While measuring the three-dimensional information or locating certain targets in a 3D space using 3D measurement technologies, identifying the material is another measurement task of great importance. Spectrometry is an effective way to analyze the composition of substances. Among various spectral analysis techniques, Raman spectroscopy is an important technical means to quickly and non-destructively characterize the structure and composition of materials [12]. Raman spectroscopy has a wide range of applications in the field of materials research. Using Raman spectroscopy to monitor average degree of smoothness and extent of structural defects during materials synthesis to study the evolution of growth kinetics to optimize growth conditions [13]. Raman spectroscopy also has great potential in microbial detection.