Real-time Reconstruction of Wide-Angle Images from Past Image-Frames with Adaptive Depth Models

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1 Real-time Reconstruction of Wide-Angle Images from Past Image-Frames with Adaptive Depth Models Kenji Honda, Naoki Hashinoto, Makoto Sato Precision and Intelligence Laboratory, Tokyo Institute of Technology {khonda, 3-D Scene generation with real images on immersive projection displays which have high-resolution and wide field of view are expected to be applied for many kinds of fields like a tele-existence and interactive communication. However, that challenge requires special devices, like a multiple camera array, or off-line processings which obstruct interactive contents. Therefore, in this research, we propose a technique that reconstructs wide view-angle images for immersive projection displays by reusing past image frames including peripheral images which are not seen from a present viewpoint. A simple 3-D model approximating the real world contributes to extracting the peripheral images from a time-series image in real-time. We apply this method to an actual CG content, and evaluate the wide view-angle images on an immersive projection display. In addition, for generation images, we performed objective and subjective evaluation and confirmed that a presence was raised Keywords : wide view-angle images real-time rendering IPT virtual reality 1 Introduction Recently, interactive contents with high-quality images are widely used in many kinds of fields. For example, Virtual Reality(VR), which provides high presence, is basically based on high quality CG technologies. Accessible games for family-used game machines are also classified into the interactive contents. By moving around the 3-D scene of the games, users can feel as if they were in the game-world. Then, the use of the environment where the wide view-angle images can be presented like immersive projection displays is tried as a method of rapidly improving the presence and the immersive feeling of such image contents [1]. In the immersive projection displays, users can feel as if they were actual in the virtual worlds by presenting images with which user s whole view is covered. However, the view-angle of image contents excluding the wide view-angle images like VR contents is fixed in most of images. In general, it is difficult to change the view-angle of images that have already existed. When images are newly generated, wide view-angle images can be made by using special devices like a multiple camera array. Moreover, when the images can be processed beforehand, they can be made wide view-angle by off-line processings. However, these techniques cannot be applied to the image of contents which changes by interactions with users, because the combination of images are infinite. Therefore, we propose a technique that reconstructs wide view-angle images by real-time processings for existing image contents with interactions like games. 2 Proposal technique 2.1 Basic concept Fig.1 shows the principle of our proposed technique. The illustration of Fig.1(a) is a walk-through

2 Fig1 Outline of proposal technique scene in a town whose sides are enclosed with the building. The depth model shown in Fig.1(b) is a simple 3-D model approximating the scene. The viewpoint of the scene is limited to move forward. Fig.1(c) shows the situation. Fig.1(c) shows tracks of the viewpoint. Information of image that does not exist in a present viewpoint exists in a past viewpoint. Information of the peripheral images that exists in the past image frames are taken by the depth model. Then, by mapping the peripheral image to the depth model, we reconstruct the scene. Then, as shown in Fig.1(d), the peripheral images are added to the present image frame shown in Fig.1(c). If viewpoint v t moves as it moves forward, wide viewangle image I t generated for viewpoint v t is shown with Eq.1. n I t = π t + P (M(π t k )) (1) k=1 where n is the number of referred image frames. The image frame at each viewpoint v t is π t. Moreover, M shows the map that decides the image of the area not contained in the present image frame from the past image frame. Matrix P projects the image information decided with M on the depth model. 2.2 Reproducibility of generated image The method of presuming the depth model introduced in 2.1 by high accuracy is one of the methods of improving the accuracy of the generated image. However, this approach is unsuitable for the realtime processings, because a lot of time is required for the depth presumption, In addition, it is known

3 that the accuracy of image information presented in the peripheral area is not demanded too much, in the case like the images obtained with the straight movement of the viewpoint. Therefore, in this proposal technique, we use a hexahedron depth model whose model is as simple as possible. The image with few senses of incompatibility in the peripheral is added to the present image frame by making this model adjust to an actual scene within the range where the real-time processings is possible. We considered that the assumption of the depth of the scene by using the simple depth model influences on the generated image. When the depth model is inadequate to approximate the depth of the actual scene, spatial discontinuity will occur in generated images. Fig.2 illustrates the cause of the spatial discontinuity. In Fig.2, the depth model cannot represent the actual scene correctly. From the viewpoint v t, P can be seen as P on the depth model. However, from the viewpoint v t 1, P corresponds to Q on the actual scene. This error becomes distortion within frame projected in the depth model. Moreover, it appears as spatial discontinuity in the part where the image extracted from different image frames is adjacent. In the peripheral area, we are more sensitive to the movement of the object than the accuracy of the image. Therefore, it is thought that the sense of incompatibility to discontinuous image in peripheral area is stronger than the distortion of the image in central area. Then, we aim to decrease the sense of incompatibility to the user by reducing spatial discontinuity in the peripheral area. 2.3 Adaptive depth model In order to eliminate spatial discontinuity, we introduce an adaptive framework which changes the depth model by observing the edge of image frames. Fig.3(a) shows observing area. In the generated image, the depth change of the scene appears in area R. Therefore, the depth change in the scene in area R is observed, and the depth model is presumed. The direction where the depth model is presumed is limited to up, down, right and left, because the hexahedron is used as a depth model. Therefore, we limit these Fig2 Appearance of point on scene observed from each viewpoint area to R m(m = top, bottom, left, right) shown in Fig.3 (b). The estimated value of the each direction is requested from the average of the motion vector obtained in each area of R m. The average vector is Fig3 calculated by Eq.2. Motion vector obtained from present image frame V m (t) = 1 s m s m n=1 V m (n, t) (2) where V m (n, t) is the motion vector of the n turn at time t obtained in each area of R m, s m (m=top,bottom, left,right) shows the number of obtained motion vec-

4 tors included in each area R m. Moreover, the error by the noise grows and the problem of the flicker of the peripheral images is caused, when the observed depth change is assumed to be a presumption value of the depth model as it is. Therefore, a smooth image is generated with the assumption of D m (t)with Eq.3. In this paper, a suitable α value is set beforehand. respectively at intervals of 20 pixel along the x axis and y axis. In addition, we assumed that the passing speed of the view-point was already-known, and a suitable α value was decided to be 0.2 with previous experiments. D m (t) = (1 α)v m (t t) + αv m (t) (3) 3 Experiments and Discussions In this paper, to improve spatial discontinuity of the generated images caused by the simple depth model, we construct an adaptive system to the scene by estimating the depth model within the range where real-time processing is possible. We apply our proposal technique to the scene made with CG, and confirm the effectiveness of the proposal technique by displaying it on the immersive projection displays. We also apply the proposal technique to the game for family-used game machines, and confirm the effectiveness of the proposal technique by displaying it on the immersive projection displays. The games mainly consist of the image contents that user moves the straight line in a virtual space with complex depth information. We experimented influence on immersive feeling by using depth model with an immersive projection displays D-vision [1]. D-vision can present human scale images with a full 180 degrees field of view. Fig.4 shows a corridor used as an experimental scene. The structure of the corridor has the depth in two stages. To confirm whether the adjustment to the changing depth is effective, we made the model whose depth changes from 2 meter to 4 meter. To match the depth model to the scene, the hexahedron of 2 m height and width was used as an initial depth model. The size of the input image frame is 512 pixel 512 pixel, and observation area R m is shown in Fig.5(b). Moreover, the template size of the blockmatching used for the movement vector search was 8 pixel 8 pixel, and the range of the search was neighborhood 30 pixel Fig4 Externals of the scene used to our experiments Fig5 Present image frame and arear 4 Results and Evaluation Fig.6 shows the result of applying the proposal technique to the scene of the above, and displaying it on the immersive projection displays. Fig.6(a) shows the image of the central area. Fig.6(b) shows the image added the peripheral area. To begin with, in the part where the scene was corresponding to the shape of the depth model, we confirmed that the peripheral image was seamlessly added. Then, we compared how the discontinuity of

5 the peripheral image that depended on the disagreement between the scene and the depth model was improved by the proposal technique, when the depth of the scene changes from 2 m to 4 m. Discontinuity is caused by the depth error in the circle in Fig.7. When the scene is not corresponding to the depth of the depth model, the result is shown by Fig.7(a). On the other hand, when we apply the proposal technique, we confirmed discontinuity was canceled as shown in Fig.7(b) because it was estimated to the depth 4 m of the scene that the depth model was almost 4 m. Moreover, Fig.8 shows result of applying proposal technique to the game, and displaying it on the immersive projection displays. Fig.8(a) shows the image of the central area. Fig.8(b) shows the image added the peripheral area. By adding the peripheral area, we confirmed the presence was obtained. 5 Conclusion In this paper, we proposed the technique that reconstructed the wide view-angle images by using information of the peripheral image that exists in the past image frame. Information of the peripheral image extracts the circumference image information by using the depth model. Though spatial discontinuity is caused by the depth error of the scene and the depth model in the generated image when the depth model is used, we improve the discontinuous part in the generation image by observing the movement vector in the generated image, and presuming the depth model dynamically. In this paper, we also confirmed the effectiveness by applying the proposal technique to actual image contents, and displaying it on an absorbed display. Our future work includes the verification of the effectiveness of the proposal technique through a lot of cases. To achieve it, it is necessary to decrease the restriction condition in this paper. For example, in this research, the passing speed of the view-point was assumed to be already-known. However, such a situation is very limited. Therefore, we want to presume the passing speed of the view-point from the Fig6 Result of displaying the generated image on the immersive projection displays Fig7 Result of the generated image when depth s change

6 1422. [4] ViewPLUS: Ladybug., [5] M.Levoy, P.Hanrahan: Light Field Rendering, Proceedings of SIGGRAPH 1996, pp.31-42(1996). [6] S.E.Chen: QuickTime VR - An Image-Based Approach to Virtual Environment Navigation., Computer Graphics(SIGGRAPH 95), pp.29-38, [7] Jaeho Ryu, Naoki Hashimoto, Makoto Sato: Influence of Resolution Degradation on Distance Estimation in Virtual Space Displaying Static and Dynamic Image., CW 2005: pp Fig8 Result of displaying the game for family-used game machines on the immersive projection displays image. Moreover, though the movement of the viewpoint is limited to the forward movements, we want to deal with the movements other than the straight line movement. References [1] Naoki Hashimoto, Shoichi Hasegawa, Makoto Sato: A Development of Multi-Projection Display D-vision, The journal of the institute of image information and television engineers, Vol.58, No.3, pp (2004). [2] Yagi,Y.: Omnidirectional Sensing and Its Applications,, IEICE Trans. Information and Systems, Vol.E82-D, No3, pp (1999). [3] J.Foote, D.Kimber: FlyCam: Practical Panoramic Video and Automatic Camera Control., IEEE Inter-national Coneference on Multimedia and Expo 2000, Aug.2000 pp.1419-

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