Stereo Vision and Wavelets/Multiwavelets Analysis: 3D.

During the image formation process of the camera, explicit 3D information about the scene or objects in the scene are lost. Therefore, 3D structure or depth information has to be inferred implicitly from the 2D intensity images. This problem is com- monly referred to as 3D reconstruction. In this work a complete 3D reconstruction algorithm is presented, capable of reconstructing dimensionally accurate 3D models of the objects, based on stereo vision and multi-resolution analysis. The developed system uses a reference depth model of the objects under observation to improve the disparity maps, estimated. Only a few features are extracted from that reference model, which are the relative location of the discontinuities and the z-dimensional extremes of objects depth. The maximum error deviation of the estimated depth along the surfaces is less than 0.5mm and along the discontinuities is less than 1.5mm. The developed system is invariant to illuminative variations, and orientation, location and scaling of the objects under consideration, which makes the developed system highly robust.

Dr. Bhatti is affiliated with Center for Intelligent Systems Research, Deakin University, Australia. He's been actively involved in R&D activities in the areas of Computer Vision, Image/Signal processing, Virtual/Augmented Reality and Haptics. Dr. bhatti has also been involved in the development of smart technologies that have been patented.