5 March 2014 On-road anomaly detection by multimodal sensor analysis and multimedia processing
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Abstract
The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.
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Fatih Orhan, P. Erhan Eren, "On-road anomaly detection by multimodal sensor analysis and multimedia processing", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 902610 (5 March 2014); doi: 10.1117/12.2038700; https://doi.org/10.1117/12.2038700
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