Technical Seminar Abstarct.docx

Kandi Bhanusree

15AG1A0516

3D Human Sensing Abstract: The Development of 3D videos on recent years realizes 3D surface capturing of human in motion as is .In this paper we introduce 3D human sensing algorithms based on 3D video .Since 3D video capturing does not require the object to attach special markers ,we can capture the original information such as body motion or viewing directions without any disturbance caused by the sensing system itself. Since 3D video is captured by conventional 2D cameras , the object is not required to attach special markers nor wear a special costume. This is a clear advantage against other motion capturing technologies , and therefore 3D video is suitable for 3D digital archiving of human motion including intangible culture assets. However, 3D video itself is merely a non-structured 3D surface data as same as pixel streams of conventional 2D video . in this paper we show how we can sense the human activity from raw 3D video.

3D VIDEO: The term “3D video “ or “free viewpoint video” includes two different approaches in literature . One approach is called “model-based” methods which reconstruct 3D shapes of the object first and then rendered them . The approach is “image-based” methods which interpolate a 2D image at a virtual camera position directly from 2D multi-viewpoint images. For 3D human sensing, model based approaches are suitable since image-based methods do not produce 3D information.The 3D shape estimation done in the model-based approaches is a classic but open problem in computer vision.