Object Localization Based on Visual Statistical Probabilistic Models
Jun Gao · 2007
Object localization in complex settings is the main process in vision task of detection and recognition.This paper presents a new method for object localization based on visual statistical probabilistic models.It is different from traditional ways of region segmentation and edge detection.First,the method can label the regions with high saliency through regional probabilistic models which were developed using the flat,texture,shading and clutter properties with different scales and then the whole object regions can be extracted by edge probabilistic models and connectivity discussion.Experiments show the approach has strong robustness and generality,because the results are in accord with visual attention properties and the background noise is lower.