Recent advances in the field of computer vision and machine learning have given birth to a generation of softwares enable to detect and track a face along a video record and eventually to measure its internal facial movements. We investigate herein on a specific task, the detection of eyebrows raising and frowning facial actions, the potential of these softwares on spontaneous, in-the-wild video corpus. We propose a tool which allow to extract eyebrows raising and frowning from the output of two state-of-the-art facial behavior analysis softwares (OpenFace and IntraFace). The evaluation performed on our manually annotated in-the-wild video corpus suggests that the tool can be used with benefits for automatic annotation purpose.