Baseline and triangulation geometry in a standard plenoptic camera

In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. The advancement of micro lenses and image sensors enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or to specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than 0:33 % for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model

A new online tool for visualization of volumetric data

This work was sponsored by the Engineering and Physical Sciences Research Council (EPSRC) UK, the Medical Research Council (MRC) UK and the Wellcome Trust

Simultaneous whole-animal 3D-imaging of neuronal activity using light field microscopy

3D functional imaging of neuronal activity in entire organisms at single cell level and physiologically relevant time scales faces major obstacles due to trade-offs between the size of the imaged volumes, and spatial and temporal resolution. Here, using light-field microscopy in combination with 3D deconvolution, we demonstrate intrinsically simultaneous volumetric functional imaging of neuronal population activity at single neuron resolution for an entire organism, the nematode Caenorhabditis elegans. The simplicity of our technique and possibility of the integration into epi-fluoresence microscopes makes it an attractive tool for high-speed volumetric calcium imaging.Comment: 25 pages, 7 figures, incl. supplementary informatio

Decoupling algorithms from schedules for easy optimization of image processing pipelines

Using existing programming tools, writing high-performance image processing code requires sacrificing readability, portability, and modularity. We argue that this is a consequence of conflating what computations define the algorithm, with decisions about storage and the order of computation. We refer to these latter two concerns as the schedule, including choices of tiling, fusion, recomputation vs. storage, vectorization, and parallelism. We propose a representation for feed-forward imaging pipelines that separates the algorithm from its schedule, enabling high-performance without sacrificing code clarity. This decoupling simplifies the algorithm specification: images and intermediate buffers become functions over an infinite integer domain, with no explicit storage or boundary conditions. Imaging pipelines are compositions of functions. Programmers separately specify scheduling strategies for the various functions composing the algorithm, which allows them to efficiently explore different optimizations without changing the algorithmic code. We demonstrate the power of this representation by expressing a range of recent image processing applications in an embedded domain specific language called Halide, and compiling them for ARM, x86, and GPUs. Our compiler targets SIMD units, multiple cores, and complex memory hierarchies. We demonstrate that it can handle algorithms such as a camera raw pipeline, the bilateral grid, fast local Laplacian filtering, and image segmentation. The algorithms expressed in our language are both shorter and faster than state-of-the-art implementations.National Science Foundation (U.S.) (Grant 0964004)National Science Foundation (U.S.) (Grant 0964218)National Science Foundation (U.S.) (Grant 0832997)United States. Dept. of Energy (Award DE-SC0005288)Cognex CorporationAdobe System

Microgeometry capture using an elastomeric sensor

We describe a system for capturing microscopic surface geometry. The system extends the retrographic sensor [Johnson and Adelson 2009] to the microscopic domain, demonstrating spatial resolution as small as 2 microns. In contrast to existing microgeometry capture techniques, the system is not affected by the optical characteristics of the surface being measured---it captures the same geometry whether the object is matte, glossy, or transparent. In addition, the hardware design allows for a variety of form factors, including a hand-held device that can be used to capture high-resolution surface geometry in the field. We achieve these results with a combination of improved sensor materials, illumination design, and reconstruction algorithm, as compared to the original sensor of Johnson and Adelson [2009].National Science Foundation (U.S.) (Grant 0739255)National Institutes of Health (U.S.) (Contract 1-R01-EY019292-01

Real-time Image Generation for Compressive Light Field Displays

With the invention of integral imaging and parallax barriers in the beginning of the 20th century, glasses-free 3D displays have become feasible. Only today—more than a century later—glasses-free 3D displays are finally emerging in the consumer market. The technologies being employed in current-generation devices, however, are fundamentally the same as what was invented 100 years ago. With rapid advances in optical fabrication, digital processing power, and computational perception, a new generation of display technology is emerging: compressive displays exploring the co-design of optical elements and computational processing while taking particular characteristics of the human visual system into account. In this paper, we discuss real-time implementation strategies for emerging compressive light field displays. We consider displays composed of multiple stacked layers of light-attenuating or polarization-rotating layers, such as LCDs. The involved image generation requires iterative tomographic image synthesis. We demonstrate that, for the case of light field display, computed tomographic light field synthesis maps well to operations included in the standard graphics pipeline, facilitating efficient GPU-based implementations with real-time framerates.United States. Defense Advanced Research Projects Agency. Soldier Centric Imaging via Computational CamerasNational Science Foundation (U.S.) (Grant IIS-1116452)United States. Defense Advanced Research Projects Agency. Maximally scalable Optical Sensor Array Imaging with Computation ProgramAlfred P. Sloan Foundation (Research Fellowship)United States. Defense Advanced Research Projects Agency (Young Faculty Award

CAVE Size Matters: Effects of Screen Distance and Parallax on Distance Estimation in Large Immersive Display Setups

International audienceWhen walking within a CAVE-like system, accommodation distance, parallax and angular resolution vary according to the distance between the user and the projection walls which can alter spatial perception. As these systems get bigger, there is a need to assess the main factors influencing spatial perception in order to better design immersive projection systems and virtual reality applications. Such analysis is key for application domains which require the user to explore virtual environments by moving through the physical interaction space. In this article we present two experiments which analyze distance perception when considering the distance towards the projection screens and parallax as main factors. Both experiments were conducted in a large immersive projection system with up to ten meter interaction space. The first experiment showed that both the screen distance and parallax have a strong asymmetric effect on distance judgments. We observed increased underestimation for positive parallax conditions and slight distance overestimation for negative and zero parallax conditions. The second experiment further analyzed the factors contributing to these effects and confirmed the observed effects of the first experiment with a high-resolution projection setup providing twice the angular resolution and improved accommodative stimuli. In conclusion, our results suggest that space is the most important characteristic for distance perception, optimally requiring about 6 to 7-meter distance around the user, and virtual objects with high demands on accurate spatial perception should be displayed at zero or negative parallax