Showing papers by "Michael G. Strintzis published in 2014"

Swarm-based motion features for anomaly detection in crowds

Abstract: In this work we propose a novel approach to the detection of anomalous events occurring in crowded scenes. Swarm theory is applied for the creation of a motion feature first introduced in this work, the Histograms of Oriented Swarm Accelerations (HOSA), which are shown to effectively capture a scene's motion dynamics. The HOSA, together with the well known Histograms of Oriented Gradients (HOGs) describing appearance, are combined to provide a final descriptor based on both motion and appearance, to effectively characterize a crowded scene. Appearance and motion features are only extracted within spatiotemporal volumes of moving pixels (regions of interest) to ensure robustness to local noise and allow the detection of anomalies occurring only in a small region of the frame. Experiments and comparisons with the State of the Art (SoA) on a variety of benchmark datasets demonstrate the effectiveness of the proposed method, its flexibility and applicability to different crowd environments, and its superiority over currently existing approaches.

Automatic generation of 3D outdoor and indoor building scenes from a single image

Abstract: In this paper, a novel approach for creating 3D models of building scenes is presented. The proposed method is fully automated and fast, and accurately reconstructs both outdoor images of a building and indoor scenes, with perspective cues in real-time, using only one image. It combines the extracted line segments to identify the vanishing points of the image, the orientation, the different planes that are depicted in the image and concludes whether the image depicts indoor or outdoor scenes. In addition, the proposed method efficiently eliminates the perspective distortion and produces an accurate 3D model of the scene without any intervention from the user. The main innovation of the method is that it uses only one image for the 3D reconstruction, while other state-of-the-art methods rely on the processing of multiple images. A website and a database of 100 images were created to prove the efficiency of the proposed method in terms of time needed for the 3D reconstruction, its automation and 3D model accuracy and can be used by anyone so as to easily produce user-generated 3D content: http://3d-test.iti.gr:8080/3d-test/3D_recon/