{'fraction_non_alphanumeric': 0.01845444059976932, 'fraction_numerical': 0.0, 'mean_word_length': 5.382352941176471, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
VideoHandles: replicating gestures to search through action-camera video

We present VideoHandles, a novel interaction technique to support rapid review of wearable video camera data by re-performing gestures as a search query. The availability of wearable video capture devices has led to a significant increase in activity logging across a range of domains. However, searching through and reviewing footage for data curation can be a laborious and painstaking process. In this paper we showcase the use of gestures as search queries to support review and navigation of video data. By exploring example self-captured footage across a range of activities, we propose two video data navigation styles using gestures: prospective gesture tagging and retrospective gesture searching. We describe VideoHandles' interaction design, motivation and results of a pilot study.