Abstract: A method of making a thermal comfort estimation of one or more human occupants in a built space in real-time is presented. The method employs one or more thermographic cameras and one or more red, green, and blue depth (RGB-D) sensors. The method has several steps. In an example, the method involves capturing thermal images of the human occupant(s) via the thermographic camera(s) and capturing RGB-D images of the human occupant(s) via the RGB-D camera(s). The method further involves extracting facial skin temperatures of the human occupant(s) using the captured thermal images and using the captured RGB-D images. And the method involves estimating the thermal comfort of the human occupant(s) using the extracted facial skin temperatures.

Abstract: A method extracts planes from three-dimensional (3D) points by first partitioning the 3D points into disjoint regions. A graph of nodes and edges is then constructed, wherein the nodes represent the regions and the edges represent neighborhood relationships of the regions. Finally, agglomerative hierarchical clustering is applied to the graph to merge regions belonging to the same plane.

Abstract: A method extracts planes from three-dimensional (3D) points by first partitioning the 3D points into disjoint regions. A graph of nodes and edges is then constructed, wherein the nodes represent the regions and the edges represent neighborhood relationships of the regions. Finally, agglomerative hierarchical clustering is applied to the graph to merge regions belonging to the same plane.