A Pseudo-3D Vision-Based Dual Approach for Machine-Awareness in Indoor Environment Combining Multi-Resolution Visual Information
Résumé
In this paper we describe a pseudo-3D vision-based dual approach for Machine-Awareness in indoor environment. The so-called duality is provided by color and depth cameras of Kinect system, which presents an appealing potential for 3D robots vision. Placing the human-machine (including human-robot) interaction as a primary outcome of the intended visual Machine-Awareness in investigated system, we aspire proffering the machine the autonomy in awareness about its surrounding environment. Combining pseudo-3D vision, and salient objects’ detection algorithms, the investigated approach seeks an autonomous detection of relevant items in 3D environment. The pseudo-3D perception allows reducing computational complexity inherent to the 3D vision context into a 2D computational task by processing 3D visual information within a 2D-images’ framework. The statistical foundation of the investigated approach proffers it a solid and comprehensive theoretical basis, holding out a bottom-up nature making the issued system unconstrained regarding prior hypothesis. We provide experimental results validating the proposed system.