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Semantic visual perception for knowledge acquisition plays an important role in human cognition, as well as in the many tasks expected to be performed by a cognitive robot. In this paper, we present a vision system designed for indoor mobile robotic systems. Inspired by recent studies on holistic scene understanding, we generate spatial information in the scene by considering plane estimation and stereo line detection coherently within a unified probabilistic framework and indicate how the resultant spatial information can be used for facilitating robust visual perception and reasoning visual elements in the scene. We also demonstrate how the proposed system facilitates and increase the robustness of two robotics applications–visual attention and continuous learning. Experiments demonstrate that our system provides plausible representation of visual objects as well as accurate spatial layout of the scene.