• Disam: Density Independent and Scale Aware Model for Crowd Counting and Localization 

      Khan, Sultan Daud; Ullah, Habib; Uzair, Mohammad; Ullah, Mohib; Ullah, Rehan; Alaya Cheikh, Faouzi (Journal article; Peer reviewed, 2019)
      People counting in high density crowds is emerging as a new frontier in crowd video surveillance. Crowd counting in high density crowds encounters many challenges, such as severe occlusions, few pixels per head, and large ...
    • Internal Emotion Classification Using EEG Signal With Sparse Discriminative Ensemble 

      Ullah, Habib; Muhammad, Uzair; Mahmood, Arif; Ullah, Mohib; Khan, Sultan Daud; Cheikh, Faouzi Alaya (Journal article; Peer reviewed, 2019)
      Among various physiological signal acquisition methods for the study of the human brain, EEG (Electroencephalography) is more effective. EEG provides a convenient, non-intrusive, and accurate way of capturing brain signals ...
    • Multi-feature-based crowd video modeling for visual event detection 

      Ullah, Habib; Islam, Ihtesham Ul; Ullah, Mohib; Afaq, Muhammad; Khan, Sultan Daud; Iqbal, Javed (Peer reviewed; Journal article, 2020)
      We propose a novel method for modeling crowd video dynamics by adopting a two-stream convolutional architecture which incorporates spatial and temporal networks. Our proposed method cope with the key challenge of capturing ...
    • TCM: Temporal Consistency Model for Head Detection in Complex Videos 

      Khan, Sultan Daud; Altamimi, Ahmed Bder; Ullah, Mohib; Ullah, Habib; Alaya Cheikh, Faouzi (Peer reviewed; Journal article, 2020)
      Head detection in real-world videos is a classical research problem in computer vision. Head detection in videos is challenging than in a single image due to many nuisances that are commonly observed in natural videos, ...