Estimation of User-Indoor Spatial Information Using Deep Neural Networks Selective Ventilation for Living Area Estimated by Deep Neural Network

Recent research on application of human body detection technology is actively under way for smart home appliances. This paper presents a method to estimate the indoor partial space with deep neural networks for air conditioner to blow air selectively into the main living area of residents. The information regarding the distance from the camera in an air conditioner is added to the 2-dimension human body detection histogram obtained from the camera to make a 3-dimensional saliency map that is preprocessed through filtering and interpolation. Deep neural network learns the human body detection saliency map to estimate the living or non-living area of the residents. Finally, temporal space estimation for human living area is performed by accumulating sequential predictions of DNN.