Segmentação de imagens de pessoas em tempo real para videoconferências

Abstract

Object segmentation has been discussed on Computer Vision and Image processing fields for quite some time. Recently, given the hardware evolution and popularization of the World Wide Web, videoconferences have been the main discussion in this area. This technique brings advantages to many fields, such as telemedicine, education (distance learning), and mainly to the business world. Many companies use videoconferences for worldwide meetings, in order to save a substantial amount o f resources. However, videoconferences still do not provide the same experience a s people have when they are in the same room. Therefore, in this paper we propose the development of a system to segment the image of a person who is attending the videoconference, in order to allow future processing that may increase the experience of being in the same room. For instance, the background of the scene could be replaced by a standard one for all participants. The proposed system uses a dynamic programming algorithm guided by energies, such as image edges, motion and probabilistic information. After extensive tests, we could conclude that the results obtained are comparable to other state of the art works and the system is able to execute in real time at 8 FPS. The advantage of the proposed system when compared to others is that no previous training is required in order to perform the segmentation