Vision-based human action recognition: An overview and real world challenges
Within a large range of applications in computer vision, Human Action Recognition has
become one of the most attractive research fields. Ambiguities in recognizing actions does …
become one of the most attractive research fields. Ambiguities in recognizing actions does …
Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
Aide: A vision-driven multi-view, multi-modal, multi-tasking dataset for assistive driving perception
Driver distraction has become a significant cause of severe traffic accidents over the past
decade. Despite the growing development of vision-driven driver monitoring systems, the …
decade. Despite the growing development of vision-driven driver monitoring systems, the …
A novel hybrid bidirectional unidirectional LSTM network for dynamic hand gesture recognition with leap motion
Due to the recent development of machine learning and sensor innovations, hand gesture
recognition systems become promising for the digital entertainment field. In this paper, we …
recognition systems become promising for the digital entertainment field. In this paper, we …
A survey on vision-based driver distraction analysis
Motor vehicle crashes are great threats to our life, which may result in numerous fatalities, as
well as tremendous economic and societal costs. Driver inattention, either distraction or …
well as tremendous economic and societal costs. Driver inattention, either distraction or …
Autovis: Enabling mixed-immersive analysis of automotive user interface interaction studies
Automotive user interface (AUI) evaluation becomes increasingly complex due to novel
interaction modalities, driving automation, heterogeneous data, and dynamic environmental …
interaction modalities, driving automation, heterogeneous data, and dynamic environmental …
A novel public dataset for multimodal multiview and multispectral driver distraction analysis: 3MDAD
Driver distraction and fatigue have become one of the leading causes of severe traffic
accidents. Hence, driver inattention monitoring systems are crucial. Even with the growing …
accidents. Hence, driver inattention monitoring systems are crucial. Even with the growing …
100-driver: a large-scale, diverse dataset for distracted driver classification
J Wang, W Li, F Li, J Zhang, Z Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Distracted driver classification (DDC) plays an important role in ensuring driving safety.
Although many datasets are introduced to support the study of DDC, most of them are small …
Although many datasets are introduced to support the study of DDC, most of them are small …
Ic3m: In-car multimodal multi-object monitoring for abnormal status of both driver and passengers
Recently, in-car monitoring has emerged as a promising technology for detecting early-
stage abnormal status of the driver and providing timely alerts to prevent traffic accidents …
stage abnormal status of the driver and providing timely alerts to prevent traffic accidents …
Deep learning-based hard spatial attention for driver in-vehicle action monitoring
Distracted driving is one of the main causes of deaths and injuries in the world. Monitoring
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …