# Locating Image Sources from Multiple Spatial Room Impulse Responses
## 3 Case Studies
### Variable Acoustics Room Arni  
As a proof of concept, the algorithm was first applied on a variable acoustics room Arri located at the Aalto acoustics laboratory. The room has a rectangular shape (dimensions \(7.9\times 5.4\times 3.2\) m) and has 55 variable acoustics panels installed on the walls and in the ceiling. The panels can be opened and closed individually, that is, the section of the surface becomes either absorptive or reflective. When all panels are closed, the reverberation time of the room is 1.6 s at mid frequencies; and when opened, the reverberation time drops to 0.4 s. These properties allow us to test the algorithm in different acoustic conditions without changing the measurement setup. The measurements were carried out as outlined in Section 2.1. As sound sources, 5 loudspeakers (model: Genelec 8331A) were set up around the room. They were oriented so that all of them pointed to the center of the room. The acoustic centers of the loudspeakers were measured w.r.t. the front faces of the panels and the floor, resulting in reference source positions. SRIRs were then measured for 10 receiver positions with a GRAS VI50-1 vector intensity probe (spacer size 5 cm). Apart from one receiver, these positions were also documented to better evaluate the algorithm performance. The SRIRs were recorded with a custom MATLAB-based recording software [18] and analyzed by the algorithm described in Section 2. The image source search results are presented in Appendix A. Figure 11 visualizes the fit results from the image source search algorithm. In this Figure, each image source consists of at least 3 ER objects. In addition, the plot grid is drawn to follow the surfaces of the acoustic panels, therefore each grid sector can be thought as a phantom image of the room. The algorithm appears to find first order image sources well and also a good number of second order image sources. The algorithm performs the best on the red sound source for which it found one third order image source as well. In the x-y perspective plot, one can find this image source in the upper-right corner three grid sectors away from the original room. The presented algorithm appears to find the floor and ceiling image sources most reliably. The detection noise in turn is apparent on the yellow and green image sources from the left wall. In addition to first and second order image sources, one can see several image source candidates that do not appear to conform to the room  
Figure 5: Legend for the result plots shown in Appendices A–C. In addition to the room image, there are 4 different markers to describe the algorithm output; (grey triangle) reference source position; (grey rectangle) reference receiver position; (numbered rectangle) estimated receiver position; and (colored marker) estimated source and image source positions. shape. Some image sources are also not found, for example, the algorithm misses the first order image sources from the -x wall for purple, blue and red sources. In Figure 10, the image sources have been aligned as described in Section 2.6. Most of the first order image sources are found to converge to relatively dense groups. Also as expected, most of the higher order image sources appear to spread instead of converge. An exception for this is the higher order reflections that are reflected by two parallel walls. These image sources appear to group as well as the first order image sources do. The algorithm was also tested with a lower ER object limit. In Figure 11, the limit is set to 2 ER objects per image source. Compared to Figure 10, the algorithm appears to find more second order image sources. The result also appears to have more detection noise than the one with the higher ER object limit. The results were also calculated for other wall absorption configurations. Figure 12 shows a case where the acoustic panels on the -y wall are open. When compared to the closed case, most of the found image sources disappear on the -y hemisphere.