Recursive image sequence segmentation by hierarchical models

This paper addresses the problem of image sequence segmentation. A technique using a sequence model based on compound random fields is presented. This technique is recursive in the sense that frames are processed in the same cadency as they are produced. New regions appearing in the sequence are detected by a morphological procedure.Peer ReviewedPostprint (published version

A real-time segmentation scheme for continuous color images

[[abstract]]A real-time segmentation scheme for continuous color images is presented in this paper. The proposed scheme consists of two main steps: (1) seed searching and region growing, (2) region-based change detection. A new color representation model, RBG-Ellipse, is proposed. This color model is similar to the HSI representation. However, the transformation between RGB and RGB-Ellipse is linear. Therefore, we are able to take advantage of noise tolerance processing as well as the efficiency in dealing with color difference computation. By using the proposed segmentation scheme, we implemented applications, (1) intelligent networked visual monitoring system and (2) user interface for distance learning to highlight the value of the proposed scheme. Users can view the results through our web site, http://www.can.tku.edu.tw.[[conferencetype]]國際[[conferencedate]]20010506~20010509[[booktype]]紙本[[conferencelocation]]Sydney, NSW, Australi

Real-time filtering and detection of dynamics for compression of HDTV

The preprocessing of video sequences for data compressing is discussed. The end goal associated with this is a compression system for HDTV capable of transmitting perceptually lossless sequences at under one bit per pixel. Two subtopics were emphasized to prepare the video signal for more efficient coding: (1) nonlinear filtering to remove noise and shape the signal spectrum to take advantage of insensitivities of human viewers; and (2) segmentation of each frame into temporally dynamic/static regions for conditional frame replenishment. The latter technique operates best under the assumption that the sequence can be modelled as a superposition of active foreground and static background. The considerations were restricted to monochrome data, since it was expected to use the standard luminance/chrominance decomposition, which concentrates most of the bandwidth requirements in the luminance. Similar methods may be applied to the two chrominance signals

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

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

Structural connectivity based on diffusion Kurtosis imaging

Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm2. For each b-value, 64 equally spaced gradient directions were sampled. For DTI fitting only images with b-value of 0 and 1000 s:mm2 were considered, whereas for the DKI fitting, the whole cohort of images were considered. To fit both DTI and DKI tensors, extract the metrics and perform tract reconstructions, the toolbox DKIu was used, and the structural connectivity analysis was accomplished using the MIBCA toolbox. Tractography results revealed, as expected, that DKI-based tractography models can resolve crossing fibres within the same voxel, which posed a limitation to the DTI-based tractography models. Structural connectivity analysis showed DKI-based networks’ ability to establish both more inter-hemisphere and intra-hemisphere connections, when compared to DTI-based networks. This may be a direct consequence of the inability to resolve crossing fibres when using the DTI model. The DKI model ability to resolve crossing fibres may provide increased sensitivity to both inter- and intra-hemispherical connections. DTI-based modularity connectograms show a distinct intra-hemispherical configuration, whereas DKI-based connectograms show an increased number of inter-hemispherical connections, with several clusters extending over both hemispheres. Global and local connectivity metrics were also studied, but yielded no conclusive results. This may be due to a lack of reproducibility of the metrics or of the small cohort of subjects considered. DKI seems to provide additional insights into structural brain connectivity by resolving crossing fibres, otherwise undetected by DTI

Measurements, Models, Systems and Design

531 s.

Novel block-based motion estimation and segmentation for video coding

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