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Majdi Sukkar, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos and Biswaranjan Acharya
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, w...
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Mohammed Razzok, Abdelmajid Badri, Ilham El Mourabit, Yassine Ruichek and Aïcha Sahel
Pedestrian tracking and detection have become critical aspects of advanced driver assistance systems (ADASs), due to their academic and commercial potential. Their objective is to locate various pedestrians in videos and assign them unique identities. Th...
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Ye-Jiao Mao, Andy Yiu-Chau Tam, Queenie Tsung-Kwan Shea, Yong-Ping Zheng and James Chung-Wai Cheung
Falls are a major problem in hospitals, and physical or chemical restraints are commonly used to ?protect? patients in hospitals and service users in hostels, especially elderly patients with dementia. However, physical and chemical restraints may be une...
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Ahmed Dirir, Henry Ignatious, Hesham Elsayed, Manzoor Khan, Mohammed Adib, Anas Mahmoud and Moatasem Al-Gunaid
Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have ...
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Qingge Ji, Haoqiang Yu and Xiao Wu
Based on tracking-by-detection, we propose a hierarchical-matching-based online and real-time multi-object tracking approach with deep appearance features, which can effectively reduce the false positives (FP) in tracking. For the purpose of increasing t...
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