Joint estimation and optimum encoding of depth field for 3-D object-based video coding

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

Utilization of improved recursive-shortest-spanning-tree method for video object segmentation

Ankara : Department of Electrical and Electronics Engineering and Institute of Engineering and Sciences, Bilkent Univ., 1997.Thesis(Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 77-81Emerging standards MPEG-4 and MPEG-7 do not standardize the video object segmentation tools, although their performance depends on them. There are a lot of still image segmentation algorithms in the literature, like clustering, split-and-merge, region merging, etc. One of these methods, namely the recursive shortest spanning tree (RSST) method, is improved so that a still image is approximated as a piecewise planar function, and well-approximated areas on the image are extracted cis regions. A novel video object segmentation algorithm, which takes the previously estimated 2-D dense motion vector field as input, and uses this improved RSST method to approximate each component of the motion vector field as a piecewise planar function, is proposed. The algorithm is successful in locating 3-D planar objects in the scene correctly, with acceptable accuracy at the boundaries. Unlike the existing algorithms in the literature, the proposed algorithm is fast, parameter-free and requires no initial guess about the segmentation result. Moreover, it is a hierarchical scheme which gives finest to coarsest segmentation results. The proposed algorithm is inserted into the current version of the emerging “Analysis Model (AM)” of the Europan COST21U'’’ project, and it is observed that the current AM is outperformed.Tuncel, ErtemM.S

Object-based 3-d motion and structure analysis for video coding applications

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1997.Thesis (Ph.D.) -- -Bilkent University, 1997.Includes bibliographical references leaves 102-115Novel 3-D motion analysis tools, which can be used in object-based video codecs, are proposed. In these tools, the movements of the objects, which are observed through 2-D video frames, are modeled in 3-D space. Segmentation of 2-D frames into objects and 2-D dense motion vectors for each object are necessary as inputs for the proposed 3-D analysis. 2-D motion-based object segmentation is obtained by Gibbs formulation; the initialization is achieved by using a fast graph-theory based region segmentation algorithm which is further improved to utilize the motion information. Moreover, the same Gibbs formulation gives the needed dense 2-D motion vector field. The formulations for the 3-D motion models are given for both rigid and non- rigid moving objects. Deformable motion is modeled by a Markov random field which permits elastic relations between neighbors, whereas, rigid 3-D motion parameters are estimated using the E-matrix method. Some improvements on the E-matrix method are proposed to make this algorithm more robust to gross errors like the consequence of incorrect segmentation of 2-D correspondences between frames. Two algorithms are proposed to obtain dense depth estimates, which are robust to input errors and suitable for encoding, respectively. While the former of these two algorithms gives simply a MAP estimate, the latter uses rate-distortion theory. Finally, 3-D motion models are further utilized for occlusion detection and motion compensated temporal interpolation, and it is observed that for both applications 3-D motion models have superiority over their 2-D counterparts. Simulation results on artificial and real data show the advantages of the 3-D motion models in object-based video coding algorithms.Alatan, A AydinPh.D