Model-based work-piece localization with salient feature selection

This paper presents a model-based work-piece localization method with salient feature selection. Model-based localization is suitable for work-piece which is one kind of the typical 3D rigid objects with less texture. However, localization based on 3D model will cause high failure rate in heavily cluttered scenes. We propose a new model-based localization method, which is integrated with salient feature selection. Two different models: 3D model and training images are used, and the salient feature selection procedure extracts the regions which may contain the objects potentially. Experiments demonstrate the effectiveness of the proposed method.