Browsing by Author "Alatan, A. Aydın"

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Open Access
Joint estimation and optimum encoding of depth field for 3-D object-based video coding
(IEEE, 1996-09) Alatan, A. Aydın; Onural, Levent
3-D motion models can be used to remove temporal redundancy between image frames. For efficient encoding using 3-D motion information, apart from the 3-D motion parameters, a dense depth field must also be encoded to achieve 2-D motion compensation on the image plane. Inspiring from Rate-Distortion Theory, a novel method is proposed to optimally encode the dense depth fields of the moving objects in the scene. Using two intensity frames and 3-D motion parameters as inputs, an encoded depth field can be obtained by jointly minimizing a distortion criteria and a bit-rate measure. Since the method gives directly an encoded field as an output, it does not require an estimate of the field to be encoded. By efficiently encoding the depth field during the experiments, it is shown that the 3-D motion models can be used in object-based video compression algorithms.
Open Access
Object based 3-D motion and structure estimation
(IEEE, 1996) Alatan, A. Aydın; Onural, Levent
Motion analysis is the most crucial part of object-based coding. A motion in 3-D environment can be analyzed better by using a 3-D motion model compared to its 2-D counterpart and hence may improve coding efficiency. Gibbs formulated joint segmentation and estimation of 2-D motion not only improves performance, but also generates robust point correspondences which are necessary for linear 3-D motion estimation algorithms. Estimated 3-D motion parameters are used to find the structure of the previously segmented objects by minimizing another Gibbs energy. Such an approach achieves error immunity compared to linear algorithms. Experimental results are promising and hence the proposed motion and structure analysis method is a candidate to be used in object-based (or even knowledge-based) video coding schemes.
Open Access
Three-dimensional motion and dense-structure estimation using convex projections
(SPIE, 1997-02) Alatan, A. Aydın; Erdem, A. Tanju; Onural, Levent
We propose a novel method for estimating the 3D motion and dense structure of an object form its two 2D images. The proposed method is an iterative algorithm based on the theory of projections onto convex sets (POCS) that involves successive projections onto closed convex constraint sets. We seek a solution for the 3D motion and structure information that satisfies the following constraints: (i) rigid motion - the 3D motion parameters are the same for each point on the object. (ii) Smoothness of the structure - depth values of the neighboring points on the object vary smoothly. (iii) Temporal correspondence - the intensities in the given 2D images match under the 3D motion and structure parameters. We mathematically derive the projection operators onto these sets and discuss the convergence properties of successive projections. Experimental results show that the proposed method significantly improves the initial motion and structure estimates.