Abstract
Panning in photography is known as the rotation of the camera horizontally. It refers to a technique whereby one follows a moving subject and takes a photo with a slow shutter speed. This creates a blurred background, while retaining sharpness in the subject. Panning shot is widely used in sports activities because it dramatically emphasizes the movement of the subject. However, it is not easy for amateur photographers to take plausible panning shots. This paper represents a digital algorithm to automatically generate panning shots using two photographs taken consecutively in time. The presented algorithm makes even novice photographers take professional panning shots very easily.
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References
London, B., Upton, J., Kobre, K., Brill, B.: Photography, 8th edn. Prentice Hall, Upper Saddle River (2004)
Jeong, K.: Paradigm shift of camera: part I. Computational photography. J. Korea Comput. Graph. Soc. 15(4), 23–30 (2009)
Raskar, R., Tumblin, J., Levoy, M., Nayer, S.: SIGGRAPH 2006 Course Notes on Computational Photography. SIGGRAPH (2006)
Yuan, L., Sun, J., Quan, L., Shum, H.Y.: Image deblurring with blurred/noisy image pairs. ACM Trans. Graph. 26(3), 1–10 (2007)
Eisemann, E., Durand, F.: Flash photography enhancement via intrinsic relighting. ACM Trans. Graph. 23(3), 673–678 (2004)
Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., Toyama, K.: Digital photography with flash and no-flash image pairs. ACM Trans. Graph. 23(3), 664–672 (2004)
Raskar, R., Tan, K., Feris, R., Yu, J., Turk, M.: Non-photorealistic camera: depth edge detection and stylized rendering using multi-flash imaging. ACM Trans. Graph. 23(3), 679–688 (2004)
Masselus, V., Peers, P., Dutré, P., Willems, Y.D.: Relighting with 4D incident light fields. ACM Trans. Graph. 22(3), 613–620 (2003)
Matusik, W., Loper, M., Pfister, H.: Progressively-refined reflectance functions from natural illumination. In: Eurographics Symposium on Rendering, pp. 299–308 (2004)
Sajadi, B., Majumder, A., Hiwada, K., Maki, A., Raskar, R.: Switchable primaries using shiftable layers of color filter arrays. ACM Trans. Graph. 30(4), 65 (2011)
Bando, Y., Chen, B., Nishita, T.: Extracting depth and matte using a color-filtered aperture. ACM Trans. Graph. 27(5), 134:1–134:9 (2008)
Cossairt, O., Zhou, C., Nayar, S.: Diffusion coded photography for extended depth of field. ACM Trans. Graph. 29(4), 31:1–31:10 (2010)
Levin, A., Fergus, R., Durand, F., Freeman, B.: Image and depth from a conventional camera with a coded aperture. ACM Trans. Graph. 26(3), 70 (2007)
Jeong, K., Kim, D., Park, S.-Y., Lee, S.: Digital shallow depth-of-field adapter for photographs. Vis. Comput. 24(4), 281–294 (2008)
Shan, Q., Jia, J., Agarwala, A.: High-quality motion deblurring from a single image. ACM Trans. Graph. 27(3), 1–10 (2008)
Fergus, R., Singh, B., Hertzmann, A., Roweis, S., Freeman, W.: Removing camera shake from a single image. ACM Trans. Graph. 24(3), 787–794 (2006)
Cho, S., Matsushita, Y., Lee, S.: Removing non-uniform motion blur from images. In: IEEE International Conference on Computer Vision, pp. 1–8 (2007)
Talvala, E., Adams, A., Horowitz, M., Levoy, M.: Veiling glare in high dynamic range imaging. ACM Trans. Graph. 26(3), 37:1–37:9 (2007)
Debevec, P., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: Proceedings of ACM SIGGRAPH, pp. 369–378 (1997)
Shan, Q., Li, Z., Jia, J., Tang, C.: Fast image/video upsampling. ACM Trans. Graph. 27(5), 153:1–153:7 (2008)
Sun, J., Xu, Z., Shum, H.: Image super-resolution using gradient profile prior. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Freeman, G., Fattal, R.: Image and video upscaling from local self-examples. ACM Trans. Graph. 28(3), 1–10 (2010)
Kopf, J., Uyttendaele, M., Deussen, O., Cohen, M.: Capturing and viewing gigapixel images. ACM Trans. Graph. 26(3), 93 (2007)
Kopf, J., Cohen, M., Lischinski, D., Uyttendaele, M.: Joint bilateral upsampling. ACM Trans. Graph. 26(3), 1–5 (2007)
Wang, Y., Hsiao, J., Sorkine, O., Lee, T.: Scalable and coherent video resizing with per-frame optimization. ACM Trans. Graph. 30(3), 88 (2011)
Wang, Y., Lin, H., Sorkine, O., Lee, T.: Motion-based video retargeting with optimized crop-and-warp. ACM Trans. Graph. 29(3), 90 (2010)
Rubinsteing, M., Shamir, A., Avidan, S.: Improved seam carving for video retargeting. ACM Trans. Graph. 27(3), 16 (2008)
Zheng, Y., Kambhamettu, C., Yu, J., Bauer, T., Steiner, K.: FuzzyMatte: A computationally efficient scheme for interactive matting. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Wang, J., Agrawala, M., Cohen, M.: Soft scissors: an interactive tool for realtime high quality matting. ACM Trans. Graph. 25(3), 9 (2008)
McGuire, M., Matusik, W., Pfister, H., Hughes, J., Durand, F.: Defocus video matting. ACM Trans. Graph. 24(3), 567–576 (2005)
Gooch, A.A., Olsen, S.C., Tumblin, J., Gooch, B.: Color2Gray: salience-preserving color removal. ACM Trans. Graph. 24(3), 1–6 (2005)
Kim, Y., Jang, C., Demouth, J., Lee, S.: Robust color-to-gray via nonlinear global mapping. ACM Trans. Graph. 28(5) (2009)
Grundland, M., Dodgson, N.A.: Decolorize: fast, contrast enhancing, color to grayscale conversion. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Vol. 40, No.11, pp. 2891–2896 (2007)
Smith, K., Landes, P., Thollot, J., Myszkowski, K.: Apparent greyscale: a simple and fast conversion to perceptually accurate images and video. Comput. Graph. Forum 27(2), 193–200 (2008)
Bai, X., Sapiro, G.: A geodesic framework for fast interactive image and video segmentation and matting. Int. J. Comput. Vis. 82(2), 113–132 (2009)
Protiere, A., Sapiro, G.: Interactive image segmentation via adaptive weighted distances. IEEE Trans. Image Process. 16, 1046–1057 (2007)
Wang, J., Cohen, M.F.: An iterative optimization approach for unified image segmentation and matting. Proc. IEEE ICCV 2005, 936–943 (2005)
Yatziv, L., Sapiro, G.: Fast image and video colorization using chrominance blending. IEEE Trans. Image Process. 15(5), 1120–1129 (2006)
Beauchemin, S.S., Barron, J.L.: The computation of optical flow. ACM Comput. Surveys 27(3), 433–466 (1995)
Weber, J., Malik, J.: Robust computation of optical-flow in a multiscale differential framework. Int. J. Comput. Vis. 14(1), 67–81 (1995)
Haussecker, H., Fleet, D.J.: Estimating optical flow with physical models of brightness variation. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 661–673 (2001)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of Imaging Understanding Workshop, pp. 121–130 (1981)
Banerjee, S., Evans, B.L.: Unsupervised automation of photographic composition rules in digital still cameras. In: Proceedings of SPIE Conference on Sensors, Color, Cameras, and Systems for Digital Photography VI, pp. 364–373 (2004)
Banerjee, S., Evans, B.L.: Unsupervised merger detection and mitigation in still images using frequency and color content analysis. In: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Proceesing, pp. 549–552 (2004)
Banerjee, S., Evans, B.L.: In-camera automation of photographic composition rules. IEEE Trans. Image Process. 16(7), 1807–1820 (2007)
Chen, L., Xie, X., Fan, X., Ma, W., Zhang, H., Zhou, H.: A visual attention model for adapting images on small displays. Multimed. Syst. 9(4), 353–364 (2003)
Suh, B., Ling, H., Bederson, B.B., Jacobs, D.W.: Automatic thumbnail cropping and its effectiveness. CHI Lett. 5(2), 95–104 (2003)
Santella, A., Agrawala, M., DeCarlo, D., Salesin, D.H., Cohen, M.F.: Gaze-based interaction for semi-automatic photo cropping. ACM Hum. Factors Comput. Syst. 771–780 (2006)
Tang, H., Joshi, N., Kapoor, A.: Learning a blind measure of perceptual image quality. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 305–312 (2011)
Lee, Y.-H., Cho, H.-J., Lee, J.-H.: Image retrieval using multiple features on mobile platform. J. Digit. Converg. 12(2), 237–243 (2014)
Lee, T.-H., Hwang, B.-H., Yun, J.-H., Choi, M.-R.: A road region extraction using OpenCV CUDA to advance the processing speed. J. Digit. Converg. 12(6), 231–236 (2014)
Kang, S.-K., Lee, J.-H.: Real-time head tracking using adaptive boosting in surveillance. J. Digit. Converg. 11(2), 243–248 (2013)
Kang, S.-K., Choi, K.-H., Chung, K.-Y., Lee, J.-H.: Object detection and tracking using Bayesian classifier in surveillance. J. Digit. Converg. 10(6), 297–302 (2012)
Kim, S.-H., Jeong, Y.-S.: Mobile image sensors for object detection using color segmentation. Cluster Comput. 16(4), 757–763 (2013)
Balafoutis, E., Panagakis, A., Laoutaris, N., Stavrakakis, I.: Study of the impact of replacement granularity and associated strategies on video caching. Cluster Comput. 8(1), 89–100 (2005)
Zhang, S., McCullagh, P., Zhang, J., Yu, T.: A smartphone based real-time daily activity monitoring system. Cluster Comput. 17(3), 711–721 (2014)
Park, R.C., Jung, H., Shin, D.-K., Kim, G.-J., Yoon, K.-H.: M2M-based smart health service for human UI/UX using motion recognition. Cluster Comput. (2014). doi:10.1007/s10586-014-0374-z
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This research was supported by the Daegu University Research Grant, 2013.
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Jeong, K., Cho, H.J. Digital panning shot generator from photographs. Cluster Comput 18, 667–676 (2015). https://doi.org/10.1007/s10586-014-0411-y
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DOI: https://doi.org/10.1007/s10586-014-0411-y