{'fraction_non_alphanumeric': 0.017758046614872364, 'fraction_numerical': 0.0, 'mean_word_length': 4.60248447204969, '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}}
Demo: Vision based smart in-car camera system for driver yawning detection

In this demo we will present a vision-based smart environment using in-car cameras that can be used for real time tracking and monitoring of a driver in order to detect the driver's drowsiness based on yawning detection. As driver fatigue and drowsiness is a major cause behind a large number of road accidents, the assistive systems that monitor a driver's level of drowsiness and alert the driver in case of vigilance can play an important role in the prevention of such accidents. Our system is built on the top of an embedded platform, called APEX™ from CogniVue Corp., that is easy and practical for installation inside a car. Moreover, we have aimed at optimizing the system in a way that it meets the real time requirements of the monitoring task while relying on the limited processing power of the embedded platform.