Hiroshi Ikeoka

Real-time depth estimation with wide detectable range using horizontal planes of sharp focus proceedings

We have been investigating a real-time depth estimation technique with a wide detectable range. This technique employs tilted optics imaging to use the variance of the depth of field on the horizontal planes of sharp focus. It requires considerably fewer multiple focus images than the conventional passive methods, e.g., the depth-from-focus and the depth-from-defocus methods. Hence, our method helps avoid the bottleneck of the conventional methods: the fact that the motion speed of optical mechanics is significantly slower than that of the image processing parts. Therefore, it is suitable for applications, such as for use in automobiles and for robotic tasks, involving depth estimation with a wide detectable range and real-time processing.

Depth estimation based on defocus blur using a single image taken by a tilted lens optics camera

In various fields such as measurement of the distance between cars and three-dimensional recognition in robotics, the depth needs to be estimated over a wide range. For this purpose, we propose a depth estimation method that uses a ground-in-focus image taken by a tilted lens optics camera. Our proposed method detects edges by local scale control. It then measures the blur amount at each edge by fitting a Gaussian blur model to them. If there are other neighboring edges, we use the linear sum of the Gaussians to increase the fitting accuracy with the blur model. We can then obtain a depth map based on the blur amount and y-coordinate of the pixel. Our experimental results showed the effectiveness of our proposed method.

Wavelength-Tunable and Bandwidth-Variable Ultra-Flat Optical Frequency Comb Block Generation From a Bismuth-Based Actively Mode-Locked Fiber Laser

We generate, for the first time and to the best of our knowledge, a tunable ultra-flat optical frequency comb (OFC) block from a 10-GHz bismuth-based actively mode-locked fiber laser. A bismuth-based erbium-doped fiber (Bi-EDF) with a length of 1.5 m and a bismuth-based highly nonlinear fiber (Bi-HNLF) with a length of 4.1 m are used as a gain medium and a spectral broadening device, respectively. We also employ a wavelength-tunable and bandwidth-variable optical filter for an intracavity filter. The center wavelength of the OFC output can be widely tuned from 1535 to 1585 nm because the Bi-EDF has a broadband gain profile. A spectrally broadened ultra-flat OFC is successfully generated by the self-phase modulation in the Bi-HNLF. By tuning the filter bandwidth, the 10-dB spectral width and the pulsewidth of the generated OFC can be widely varied from 0.23 to 2.4 nm and from 3 to 20.1 ps, respectively. The fiber ring cavity is as short as 17.8 m. For the entire tuning ranges, the proposed bismuth-based tunable ultra-flat OFC generator also realizes stable bit-error-free mode-locking operation.

Distance estimation using two different-aperture images obtained by tilted lens optics camera

In this paper, we propose a distance estimation method using tilted lens optics. Our proposed method uses two input images: one is an all-in-focus image, and the other is a ground-in-focus image. The method estimates a distance value for each pixel by comparing the amount of blur between the ground-in-focus image and multi-focus images that are synthesized by applying a Gaussian filter to the all-in-focus image. As our method needs only two input images and simple calculations, it is suitable for distance estimation applications that require a wide detection range and real-time processing, such as robotics and automotive tasks.

High Speed Depth Estimation Using Tilted Focal Planes

We have been investigating the depth estimation method by depth from focus (DFF) using tilted focal planes imaging. This method uses fewer multiple focus images than the traditional methods. Therefore, it is suitable for high speed depth estimation accomplished by a smart image sensor.

Wide range depth estimation from two blurred images with tilted lens optics

It is possible to make depth measurements with comparative ease using the stereo camera method. However, because a lengthy baseline is required, this technique is not readily applicable to in-vehicle tasks, which need to be robust to accommodate various disturbances. Also, it is impossible to use conventional monocular-camera methods over a wide visible range in real-time. Therefore, this paper proposes a wide-range depth estimation method based on blurred images from a monocular imaging device. Our proposed method obtains two separately focused images for one scene spectroscopically. Our method inclines the plane of sharp focus (POF) and the depth of field (DOF) in the desired direction of depth measurement using tilted lens optics. Then, a depth estimation can be obtained from the blur rate between two pixels at the position of interest in each image. Our method does not require a long baseline, yet offers a wide detectable range in real-time, making it viable for in-vehicle tasks. Then, by comparing the estimation accuracy of our method to the simple stereo method, this paper demonstrates the effectiveness of our approach.

Depth estimation for automotive with tilted optics imaging

We have been investigating a depth estimation system for use in automobile applications. Conventional methods with stereo camera are too sensitive to slight variations of baseline length due to vibration and temperature. Conversely, the method that uses a monocular camera by focusing cannot provide a balance between wide-area estimation and realtime estimation. Therefore, we proposed a novel method that adopts tilted lens optics. In this method, the plane of sharp focus (POF) lies and the depth of field (DOF) enlarges toward the depth direction. Herein, we can obtained depth values at each pixel from the sharpness values of only two tilted optics images using monocular camera system with spectroscopic.

Depth Estimation Using Variant of Depth of Field by Horizontal Planes of Sharp Focus

We have been investigating depth estimation techniques using variant of depth of field (DOF) by tilted optics imaging. These techniques can be applied for robotic and automation tasks, because it needs extremely fewer multiple focus images for depth estimation than the conventional passive methods. Hence, our method gets rid of the bottleneck of passive methods with a single camera; the motion speed of optical mechanics is very slower than that of image processing parts. Therefore, it is suitable for the high speed depth estimation like real-time processing accomplished by hardware such as a smart image sensor or an FPGA.