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While motion capture is rapidly becoming the gold standard for research on the intricacies of co-speech gesture and its relationship to speech, traditional marker-based motion capture technology is not always feasible, meaning researchers must code video data manually. We compare two methods for coding co-speech gestures of the hands and arms in video data of spontaneous speech: manual coding and semi-automated coding using OpenPose, a markerless motion capture software. We provide a comparison of the temporal alignment of gesture apexes based on video recordings of interviews with speakers of Medumba (Grassfields Bantu). Our results show a close correlation between the computationally calculated apexes and our hand-annotated apexes, suggesting that both methods are equally valid for coding video data. The use of markerless motion capture technology for gesture coding will enable more rapid coding of manual gestures, while still allowing