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.
CITATION STYLE
Fraihat, H., Madani, K., & Sabourin, C. (2017). A pseudo-3D vision-based dual approach for machine-awareness in indoor environment combining multi-resolution visual information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10306 LNCS, pp. 644–654). Springer Verlag. https://doi.org/10.1007/978-3-319-59147-6_55
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