720p, Full-HD, 4K, 8K, …, display resolutions are increasing heavily over the past time. However, many video streaming providers are currently streaming videos with a maximum of 4K/UHD-1 resolution. Considering that normal video viewers are enjoying their videos in typical living rooms, where viewing distances are quite large, the question arises if more resolution is even recognizable. In the following paper we will analyze the problem of UHD perceptibility in comparison with lower resolutions. As a first step, we conducted a subjective video test, that focuses on short uncompressed video sequences and compares two different testing methods for pairwise discrimination of two representations of the same source video in different resolutions. We selected an extended stripe method and a temporal switching method. We found that the temporal switching is more suitable to recognize UHD video content. Furthermore, we developed features, that can be used in a machine learning system to predict whether there is a benefit in showing a given video in UHD or not. Evaluating different models based on these features for predicting perceivable differences shows good performance on the available test data. Our implemented system can be used to verify UHD source video material or to optimize streaming applications.