亀田 裕介

This paper proposes a spatially scalable image coding scheme based on a non-linear image resizing technique called seam carving. In this scheme, the original size image is reconstructed from the reduced size one with a help of side information including paths of the removed seams. To reduce the amount of the side information, evenly spaced multiple seams are removed simultaneously at the resizing stage.

In this paper, we propose a rotation invariant method for human detection from top view images. In the method, local features based on Histogram of Oriented Gradients (HOG) are defined based on polar coordinates. In addition, two dimensional histograms are calculated from pairs of neighboring pels to enhance robustness against small rotation.

We previously proposed a semi-automatic 2D-3D conversion method for still images. The method propagates depth information, which is partially given by the user as an input, to a whole image based on local similarity of image values. Therefore, the propagation process must be sufficiently fast for interactive operation. In this paper, we accelerate this process by using a kind of distance transform.

This paper describes a new intra prediction method which is designed to exploit inter-block correlations for DCT based image coding. By changing a coding process of DCT coefficients from block-wise order to coefficient-wise one, the method can benefit from interpolative prediction in almost all blocks.

We previously proposed a block-adaptive spatio-temporal prediction method for video coding. In this method, multiple predictors that minimize sum of squared errors are designed for each frame. However, such a least squares approach does not necessarily improve the coding performance. In this paper, we introduce a DCT domain soft shrinkage process to reduce the number of non-zero DCT coefficients to be encoded.

For the purpose of user interface or marketing, estimation of gaze directions by a noncontact measurement device has been studied in recent years. This paper describes an eigenspace-based method which estimates horizontal and vertical angles of the gaze directionfrom eye region images.

As an efficient way for archiving the existing video contents compressed by the old standard, we are developing a lossless re-encoding scheme for MPEG-1 video. In this paper, simplified probability models used for arithmetic coding of DCT coefficients are investigated to reduce computation time needed for our coding scheme.

This paper proposes an efficient lossless coding method for color quantized images each of which consists of an array of indices and corrsponding RGB values of representative colors. In the conventional methods, predictive coding techniques developed for lossless image coding are often applied to the array of indices. On the other hand, our method directly predicts a 3D position of each index in a RGB color space to accurately estimate its occurrence probability.

We previously proposed a new type of lossy image coding scheme whose compressed data can be losslessly converted into JPEG bitstreams. In this paper, perceptual image quality of our coding scheme is improved by taking account of spatial frequency characteristics of the human visual system. Results of our subjective quality assessment test demonstrate that perceptual quality of the reconstructed images is certainly improved.

We propose a stable computation scheme for variational scene-flow computation. Scene flow is a velocity field on a stereo image sequence and represents apparent motions and disparity changes. The stability condition of the proposed scheme is independent of images and regularization coefficients in the variational problem.

We previously proposed a lossy coding scheme based on recursive-type intra prediction and discrete sine transform (DST) for monochrome still images. In this paper, we extend the scheme to RGB 4:4:4 format color images. In order to exploit intra- and inter-color correlations, the already encoded color signals are simultaneously used in the prediction process.

Recently, the coding technology of multi-view video plus depth has been developed to implement 3D video applications such as Free Viewpoints Television. Because depth maps tend to have smooth value within an object and have strong edges between objects, it is efficient to encode depth maps by a region-oriented manner. In this paper, we introduce a segmentation method based on Voronoi diagrams to reduce the amount of information on the region shapes. Moreover, we propose a plane approximation to the depth values in each region.

In the previous work, we proposed a lossless coding method which dynamically models probability density function (PDF) of image values pel-by-pel. In this method, the PDF model is defined as sum of the generalized Gaussian functions (GGFs) whose peak positions are given by examples collected from causal neighbors. However, the shapes of the GGFs were fixed for each image. In this paper, we introduce a technique of context modeling to adaptively control the respective shapes.

Directional intra prediction currently used in H.264/AVC and H.265/HEVC is unsuitable for curved textures because predicted values are always extrapolated along straight lines in a given direction. In this paper, we propose a new prediction technique which enables interpolative prediction along circular curves defined by two kinds of parameters.

We previously proposed a block-based adaptive prediction method for efficient coding of color video signals in RGB 4:4:4 format. The method exploits temporal, spatial and inter-color correlations of color video signals simultaneously. In this paper, we extend the temporal prediction to use multiple reference frames in a similar way to the variable block size bi-prediction.

We evaluate the performance of the proposed stable computation scheme for the variational scene-flow estimation, whose stability is independent of the regularization parameter and stereo image sequences. The results show that the proposed method gives smaller endpoint error than the previous method.

Recently, a technique of visual cryptography which reveals a secret image by overlaying two other images has attracted attention. As an application of this technique, we propose a method to embed given QR codes in halftone images which can be recognized as the same natural image.

変分法に基づくオプテイカルフロー計算は，オプテイカルフローの条件から成る最小化問題の解として見かけの速度場を求める手法である．単純な画像列には，その動きを多義的に解釈できる場合が存在する．本論文では，動きの多義解釈について，変分法に基づくオプティカルフロー計算法の観点から考察し，オプティカルフローの条件式と境界条件を変えることによって動きの多義解釈が－部説明可能であること示す．数値実験では，各条件の元で計算されたオプテイカルフローが多義解釈の一部に相当することを示している．本研究により，これまで心理実験によって説明されてきた動きの多義解釈を数理的に説明できることを示す．Most of the methods to compute optical flows are variational-technique-based methods, which estimate appearance velocity fields by solving an energy minimization problem conposed of some conditions of the velocity fields. For simple images, sometimes the appearance motions of the images can be recognized ambiguously. In this paper, we discuss about the ambiguity of appearance motions form the viewpoint of the variational-technique-based method and show that the ambiguity is partially explicable by the theory of the method. Numerical experiments show that the optical flows computed under each condition correspond to the some of the ambiguity. Prom the results, we show that the theory of the variational-technique-based method can explain mathematically the ambiguities which have been represented by psycholigy experiments in the past.

オプテイカルフロー計算法の多くは変分法に基づく手法であり，画像関数が時空間的連続性を持つことと見かけの動きが小さいことを仮定している．時空間微分の離散化誤差の観点において，微分の差分近似精度の問題があるため，オプテイカルフローの適切な解像度は画像の解像度とフレームレートに依存する．つまり，低フレームレート画像の場合，オプティカルフローの適切な解像度は画像の解像度よりも小さくなるはずである．しかし，多くの従来手法はオプテイカルフローを画像と同じ解像度で求めている．したがって，解像度が高すぎる場合，画像のダウンサンプリングは変分法に基づく手法に対して有効に働く．本論文では，オプテイカルフローの誤差解析の観点から，変分法に基づく手法を用いたオプティカルフロー推定の適切な解像度について解析する．適切な解像度を推定するために，画像の解像度から構築した階層的構造を用いる．数値計算結果は低フレームレート画像の解像度を下げることが変分法に基づくオプテイカルフロー計算において有効であることを示している．Most of the methods to compute optical flows are variational-technique based methods, which assume that image functions have spatiotemporal continuities and also the appearance motions are small. In the viewpoint of the discrete errors of spatial- and time-differentials, the appropriate resolution of optical flow depends on both the resolution and frame rate of images since there is a problem about the accuracy of the discrete approximations of derivatives. Therefore, in the case of low frame-rate images, the appropriate resolution of optical flow should be lower than the resolution of images. However, many traditional methods estimate optical flow with same resolution of the images. Therefore, if the resolution is too high, down-sampling the images is effective to variational-technique based methods. In this paper, we analyze the appropriate resolutions of optical flows estimated by variational optical-flow computations from the viewpoint of the error analysis of optical flows. To analyze appropriate resolutions, we use hierarchical structures constructed from the multi-resolutions of images. Numerical results show that decreasing image resolutions is effective to compute optical flows by vaxiational optical-flow computations in low frame-rate sequences.