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Occlusion-based depth ordering on monocular images with binary partition tree
Palou Visa, Guillem; Salembier Clairon, Philippe Jean
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
This paper proposes a system to relate objects in an image using occlusion cues and arrange them according to depth. The system does not rely on any a priori knowledge of the scene structure and focuses on detecting specific points, such as T-junctions, to infer the depth relationships between objects in the scene. The system makes extensive use of the Binary Partition Tree (BPT) as the segmentation tool jointly with a new approach for T-junction estimation. Following a bottom-up strategy, regions (initially individual pixels) are iteratively merged until only one region is left. At each merging step, the system estimates the probability of observing a T-junction which is a cue of occlusion when three regions meet. When the BPT is constructed and the pruning is performed, this information is used for depth ordering. Although the proposed system only relies on one low-level depth cue and does not involve any learning process, it shows similar performances than the state of the art.
Àrees temàtiques de la UPC::Enginyeria electrònica i telecomunicacions::Processament del senyal::Processament de la imatge i del senyal vídeo
Image processing -- Digital techniques
Color computer graphics
Imatges -- Processament -- Tècniques digitals
Color -- Processament de dades
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