State-of-the Art Motion Estimation in the Context of 3D TV
This work addresses motion estimation challenges for 3D TV applications, but it appears to be an incremental review or survey rather than presenting new research.
The chapter investigates the role of motion compensation/estimation in 3D TV, highlighting how motion vectors can enhance various processes like acquisition, compression, and rendering, with a focus on shape-from-motion techniques for 3D shape extraction from single camera data.
Progress in image sensors and computation power has fueled studies to improve acquisition, processing, and analysis of 3D streams along with 3D scenes/objects reconstruction. The role of motion compensation/motion estimation (MCME) in 3D TV from end-to-end user is investigated in this chapter. Motion vectors (MVs) are closely related to the concept of disparities, and they can help improving dynamic scene acquisition, content creation, 2D to 3D conversion, compression coding, decompression/decoding, scene rendering, error concealment, virtual/augmented reality handling, intelligent content retrieval, and displaying. Although there are different 3D shape extraction methods, this chapter focuses mostly on shape-from-motion (SfM) techniques due to their relevance to 3D TV. SfM extraction can restore 3D shape information from a single camera data.