While capturing images of a scene, the relative motion between the camera and the scene during exposure leads to motion-blur in images. The convolution model for motion-blur is applicable only when the camera motion is restricted to in-plane translations. Blur arising due to rotation and out-of-plane translation of camera cannot be modeled using convolution with a single blur kernel [3, 5, 6]. ...

In this paper we consider the problem of multi-person detection from the perspective of a head mounted stereo camera. As pedestrians close to the camera cannot be detected by classical full-body detectors due to strong occlusion, we propose a stereo depth-template based detection approach for close-range pedestrians. We perform a sliding window procedure, where we measure the similarity between...

In the depth from defocus (DFD) method, two defocused images of a scene are obtained by capturing the scene with different sets of camera parameters. An arbitrary selection of the camera settings can result in observed images whose relative blurring is insufficient to yield a good estimate of the depth. In this paper, we study the effect of the degree of relative blurring on the accuracy of the...

This short paper proposes a method for computing depth maps from multiple satellite cameras and fusing them to an enhanced one for the principal camera of a movie production. Additional precision is gathered from optionally adding a Time-of-Flight camera. The proposed algorithm is a generalization of the PatchMatch Stereo algorithm [1]. It calculates multiple stereo depth maps without the need ...

We combine a low resolution Time-Of-Flight (TOF) depth image camera based on Photonic Mixer Devices with two standard cameras in a stereo configuration. We show that this approach is useful even without accurate calibration. In a graph cut approach, we use depth information from the low resolution TOF camera to initialise the domain, and colour information for accurate depth discontinuities in ...

In this paper, a three-dimensional (3D) object moving direction and velocity estimation method is presented using a dual off-axis color-filtered aperture (DCA)-based computational camera. Conventional object tracking methods provided only two-dimensional (2D) states of an object in the image for the target representation. The proposed method estimates depth information in the object region from...

In this paper, a feature-based technique for the camera pose estimation in a sequence of wide-baseline images has been proposed. Camera pose estimation is an important issue in many computer vision and robotics applications, such as, augmented reality and visual SLAM. The proposed method can track captured images taken by hand-held camera in room-sized workspaces with maximum scene depth of 3-4...

We present an algorithm that simultaneously calibrates a color camera, a depth camera, and the relative pose between them. The method is designed to have three key features that no other available algorithm currently has: accurate, practical, applicable to a wide range of sensors. The method requires only a planar surface to be imaged from various poses. The calibration does not use color or de...