Disparity matching and object extraction of stereoscopic video are critical procedures for many computer vision applications. Current research in this area is mostly focused on algorithm design for software implementation and the coding efficiency is not acceptable for many real-time applications. To overcome the problems and further improve efficiency, several hardware oriented methods and architectures are proposed. First, an improved disparity matching method referred as two-level hybrid disparity estimation is proposed which is designed for stereoscopic video and has low computational complexity and good performance. Then a new segmentation algorithm for the depth map previously obtained referred as average but keep boundary (ABKB) is proposed. Both of these algorithms are combined with an existing mean shift color segmentation algorithm to design a high speed video object extraction unit.
|Original language||English (US)|
|Number of pages||4|
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|State||Published - Dec 1 2005|
|Event||IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan|
Duration: May 23 2005 → May 26 2005