Background modeling on depth video sequences using self-organizing retinotopic maps
Mario Ignacio Chacon-Murguia, Oscar Alejandro Chavez-Montes, Juan A. Ramírez-Quintana · 2016
A depth video background modeling method based on a cascade retinotopic map is presented in this paper. The proposed scheme is intended to be used in a virtual therapy system to attend children with different restricted arm movement. The proposed method involves two retinotopic maps with different background modeling capacities. The neural network scheme was tested under several laboratory and real world therapy scenarios. Regarding the findings, the model achieved an acceptable performance on both types of scenarios, and showed its potential to solve bootstrapping conditions, deal with different patient body positions, and visual interference commonly found in therapy sessions.