In our daily life people encounter many social interactions, for example in the supermarket, at work and in schools. Currently the most reliable way to find social interactions in groups, is to manually annotate the data. Manual annotation takes a lot of time and human resources and as the information stream goes faster and faster, the manual labour cannot keep up. Therefore an automated program to replace this is desirable. One method to automate this, is by looking at the proximity of people, which has been done by Dikker [1]. The results look promising, however they are sensitive to errors. The F1-score (equation 3) is only 0.625 and the precision (equation 5) is 0.696. This means that there are still a lot of false positives. With orientation data one can determine if the people in question are facing each other before they are assigned to be in social interaction. With a view frustum (cone shape) it can be determined who are facing at each other by checking if the cones overlap. This cone can take different sizes, making the view area bigger or smaller. Because the absolute rotation were only used, it was used to find out who cannot face each other. Using the proximity results as a baseline, the impossible orientations were removed. With the goal to reduce the amount of false positives. From the results it can be concluded that a small cone will perform worse compared to the baseline. The bigger the angle of the cone becomes, the closer it gets to the results from Dikker [1]. However, in none of the results it turns out that using absolute orientations improves the current work significantly.