TY - RPRT A1 - Amano, Toshiyuki A1 - Bimber, Oliver A1 - Grundhöfer, Anselm T1 - Appearance Enhancement for Visually Impaired with Projector Camera Feedback N2 - Visually impaired is a common problem for human life in the world wide. The projector-based AR technique has ability to change appearance of real object, and it can help to improve visibility for visually impaired. We propose a new framework for the appearance enhancement with the projector camera system that employed model predictive controller. This framework enables arbitrary image processing such as photo-retouch software in the real world and it helps to improve visibility for visually impaired. In this article, we show the appearance enhancement result of Peli's method and Wolffshon's method for the low vision, Jefferson's method for color vision deficiencies. Through experiment results, the potential of our method to enhance the appearance for visually impaired was confirmed as same as appearance enhancement for the digital image and television viewing. KW - Maschinelles Sehen KW - Projector Camera System KW - Model Predictive Control KW - Visually Impaired Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20100106-14974 ER - TY - JOUR A1 - Bimber, Oliver A1 - Iwai, Daisuke T1 - Superimposing Dynamic Range JF - Eurographics 2009 N2 - Replacing a uniform illumination by a high-frequent illumination enhances the contrast of observed and captured images. We modulate spatially and temporally multiplexed (projected) light with reflective or transmissive matter to achieve high dynamic range visualizations of radiological images on printed paper or ePaper, and to boost the optical contrast of images viewed or imaged with light microscopes. KW - CGI KW - Computer graphics KW - Image processing KW - Computer vision KW - 54.73 Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20120130-15325 ER - TY - RPRT A1 - Exner, David A1 - Bruns, Erich A1 - Kurz, Daniel A1 - Grundhöfer, Anselm A1 - Bimber, Oliver T1 - Fast and Reliable CAMShift Tracking N2 - CAMShift is a well-established and fundamental algorithm for kernel-based visual object tracking. While it performs well with objects that have a simple and constant appearance, it is not robust in more complex cases. As it solely relies on back projected probabilities it can fail in cases when the object's appearance changes (e.g. due to object or camera movement, or due to lighting changes), when similarly colored objects have to be re-detected or when they cross their trajectories. We propose extensions to CAMShift that address and resolve all of these problems. They allow the accumulation of multiple histograms to model more complex object appearance and the continuous monitoring of object identi- ties to handle ambiguous cases of partial or full occlusion. Most steps of our method are carried out on the GPU for achieving real-time tracking of multiple targets simultaneously. We explain an ecient GPU implementations of histogram generation, probability back projection, im- age moments computations, and histogram intersection. All of these techniques make full use of a GPU's high parallelization. KW - Bildverarbeitung KW - CAMShift KW - Kernel-Based Tracking KW - GPU Programming KW - CAMShift KW - Kernel-Based Tracking KW - GPU Programming Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20091217-14962 ER - TY - RPRT A1 - Grundhöfer, Anselm A1 - Bimber, Oliver T1 - Dynamic Bluescreens N2 - Blue screens and chroma keying technology are essential for digital video composition. Professional studios apply tracking technology to record the camera path for perspective augmentations of the original video footage. Although this technology is well established, it does not offer a great deal of flexibility. For shootings at non-studio sets, physical blue screens might have to be installed, or parts have to be recorded in a studio separately. We present a simple and flexible way of projecting corrected keying colors onto arbitrary diffuse surfaces using synchronized projectors and radiometric compensation. Thereby, the reflectance of the underlying real surface is neutralized. A temporal multiplexing between projection and flash illumination allows capturing the fully lit scene, while still being able to key the foreground objects. In addition, we embed spatial codes into the projected key image to enable the tracking of the camera. Furthermore, the reconstruction of the scene geometry is implicitly supported. KW - Association for Computing Machinery / Special Interest Group on Graphics KW - CGI KW - Maschinelles Sehen KW - Farbstanzen KW - Erweiterte Realität KW - Projektion KW - Chroma Keying KW - Bildmischung KW - Augmented Reality KW - Projection KW - Chromakeying KW - Compositing Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20080226-13016 ER - TY - RPRT A1 - Bimber, Oliver A1 - Iwai, Daisuke T1 - Superimposing Dynamic Range N2 - We present a simple and cost-efficient way of extending contrast, perceived tonal resolution, and the color space of static hardcopy images, beyond the capabilities of hardcopy devices or low-dynamic range displays alone. A calibrated projector-camera system is applied for automatic registration, scanning and superimposition of hardcopies. We explain how high-dynamic range content can be split for linear devices with different capabilities, how luminance quantization can be optimized with respect to the non-linear response of the human visual system as well as for the discrete nature of the applied modulation devices; and how inverse tone-mapping can be adapted in case only untreated hardcopies and softcopies (such as regular photographs) are available. We believe that our approach has the potential to complement hardcopy-based technologies, such as X-ray prints for filmless imaging, in domains that operate with high quality static image content, like radiology and other medical fields, or astronomy. KW - Bildverarbeitung KW - CGI KW - Computergraphik KW - Kontrast KW - Projektor-Kamera Systeme KW - Hoher Dynamikumfang KW - Contrast KW - Projector-Camera Systems KW - High Dynamic Range Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20080422-13585 ER - TY - JOUR A1 - Bruns, Erich A1 - Bimber, Oliver T1 - Phone-to-Phone Communication for Adaptive Image Classification N2 - In this paper, we present a novel technique for adapting local image classifiers that are applied for object recognition on mobile phones through ad-hoc network communication between the devices. By continuously accumulating and exchanging collected user feedback among devices that are located within signal range, we show that our approach improves the overall classification rate and adapts to dynamic changes quickly. This technique is applied in the context of PhoneGuide – a mobile phone based museum guidance framework that combines pervasive tracking and local object recognition for identifying a large number of objects in uncontrolled museum environments. KW - Peer-to-Peer-Netz KW - Bilderkennung KW - Museumsführer KW - Ad-hoc-Netz KW - Phone-to-phone communication KW - adaptive image classification KW - mobile ad-hoc networks KW - museum guidance system Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20080722-13685 ER - TY - RPRT A1 - Grosse, Max A1 - Bimber, Oliver T1 - Coded Aperture Projection N2 - In computer vision, optical defocus is often described as convolution with a filter kernel that corresponds to an image of the aperture being used by the imaging device. The degree of defocus correlates to the scale of the kernel. Convolving an image with the inverse aperture kernel will digitally sharpen the image and consequently compensate optical defocus. This is referred to as deconvolution or inverse filtering. In frequency domain, the reciprocal of the filter kernel is its inverse, and deconvolution reduces to a division. Low magnitudes in the Fourier transform of the aperture image, however, lead to intensity values in spatial domain that exceed the displayable range. Therefore, the corresponding frequencies are not considered, which then results in visible ringing artifacts in the final projection. This is the main limitation of previous approaches, since in frequency domain the Gaussian PSF of spherical apertures does contain a large fraction of low Fourier magnitudes. Applying only small kernel scales will reduce the number of low Fourier magnitudes (and consequently the ringing artifacts) -- but will also lead only to minor focus improvements. To overcome this problem, we apply a coded aperture whose Fourier transform has less low magnitudes initially. Consequently, more frequencies are retained and more image details are reconstructed. KW - Association for Computing Machinery / Special Interest Group on Graphics KW - CGI KW - Projektion KW - Blende Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20080227-13020 ER - TY - JOUR A1 - Brombach, Benjamin A1 - Bruns, Erich A1 - Bimber, Oliver T1 - Subobject Detection through Spatial Relationships on Mobile Phones N2 - We present a novel image classification technique for detecting multiple objects (called subobjects) in a single image. In addition to image classifiers, we apply spatial relationships among the subobjects to verify and to predict locations of detected and undetected subobjects, respectively. By continuously refining the spatial relationships throughout the detection process, even locations of completely occluded exhibits can be determined. Finally, all detected subobjects are labeled and the user can select the object of interest for retrieving corresponding multimedia information. This approach is applied in the context of PhoneGuide, an adaptive museum guidance system for camera-equipped mobile phones. We show that the recognition of subobjects using spatial relationships is up to 68% faster than related approaches without spatial relationships. Results of a field experiment in a local museum illustrate that unexperienced users reach an average recognition rate for subobjects of 85.6% under realistic conditions. KW - Objekterkennung KW - Smartphone KW - Subobjekterkennung KW - Räumliche Beziehungen KW - Neuronales Netz KW - Museumsführer KW - Subobject Detection KW - Spatial Relationships KW - Neural Networks KW - Museum Guidance Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20081007-14296 ER - TY - RPRT A1 - Bimber, Oliver T1 - Superimposing Dynamic Range N2 - Replacing a uniform illumination by a high-frequent illumination enhances the contrast of observed and captured images. We modulate spatially and temporally multiplexed (projected) light with reflective or transmissive matter to achieve high dynamic range visualizations of radiological images on printed paper or ePaper, and to boost the optical contrast of images viewed or imaged with light microscopes. KW - Bildverarbeitung KW - CGI KW - Computergraphik KW - Kontrast KW - Projektor-Kamera Systeme KW - Hoher Dynamikumfang KW - Mikroskopie KW - Contrast KW - Projector-Camera Systems KW - High Dynamic Range KW - Microscopy Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20090303-14662 ER - TY - JOUR A1 - Grundhöfer, Anselm A1 - Seeger, Manja A1 - Häntsch, Ferry A1 - Bimber, Oliver T1 - Coded Projection and Illumination for Television Studios N2 - We propose the application of temporally and spatially coded projection and illumination in modern television studios. In our vision, this supports ad-hoc re-illumination, automatic keying, unconstrained presentation of moderation information, camera-tracking, and scene acquisition. In this paper we show how a new adaptive imperceptible pattern projection that considers parameters of human visual perception, linked with real-time difference keying enables an in-shot optical tracking using a novel dynamic multi-resolution marker technique KW - Association for Computing Machinery / Special Interest Group on Graphics KW - CGI KW - Maschinelles Sehen KW - Virtuelle Studios KW - Erweiterte Realität KW - Kamera Tracking KW - Projektion KW - Virtual Studios KW - Augmented Reality KW - Camera Tracking KW - Projection Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-8005 ER -