{'fraction_non_alphanumeric': 0.015625, 'fraction_numerical': 0.0, 'mean_word_length': 5.00625, '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}}
Digital human face detection in video sequences via a physiological signal analysis

Abstract. Imagine a future in which computer-generated (CG) human characters become almost indistinguishable from real humans. It is not that far away. Real-time rendering of photorealistic facial animation is just around the corner. To prepare for this world in which CG content will be intermingled with the natural, there is a fundamental need to understand how human beings can preserve the awareness of what is real and what is not. We present a methodology for distinguishing real and CG human faces within the context of multimedia forensics, by exploiting the heart rate as the discriminating feature. The underlying idea is that humans always present a pulse signal that can be automatically extracted from a video sequence depicting their face, while this is not the case for virtual humans. Experimental validation shows the effectiveness of the proposed solution.