Current 3-D video (3DV) technology is based on stereo systems. These systems use stereo video coding for pictures delivered by two input cameras. Typically, such stereo systems only reproduce these two camera views at the receiver and stereoscopic displays for multiple viewers require wearing special 3-D glasses. On the other hand, emerging autostereoscopic multiview displays emit a large numbers of views to enable 3-D viewing for multiple users without requiring 3-D glasses. For representing a large number of views, a multiview extension of stereo video coding is used, typically requiring a bit rate that is proportional to the number of views. However, since the quality improvement of multiview displays will be governed by an increase of emitted views, a format is needed that allows the generation of arbitrary numbers of views with the transmission bit rate being constant. Such a format is the combination of video signals and associated depth maps. The depth maps provide disparities associated with every sample of the video signal that can be used to render arbitrary numbers of additional views via view synthesis. This paper describes efficient coding methods for video and depth data. For the generation of views, synthesis methods are presented, which mitigate errors from depth estimation and coding.

3-D Video Representation Using Depth Maps

Autonomous mobile robots are becoming more prominent in recent time because of their relevance and applications to the world today. Their ability to navigate in an environment without a need for physical or electro-mechanical guidance devices has made it more promising and useful. The use of autonomous mobile robots is emerging in different sectors such as companies, industries, hospital, institutions, agriculture and homes to improve services and daily activities. Due to technology advancement, the demand for mobile robot has increased due to the task they perform and services they render such as carrying heavy objects, monitoring, search and rescue missions, etc. Various studies have been carried out by researchers on the importance of mobile robot, its applications and challenges. This survey paper unravels the current literatures, the challenges mobile robot is being faced with. A comprehensive study on devices/sensors and prevalent sensor fusion techniques developed for tackling issues like localization, estimation and navigation in mobile robot are presented as well in which they are organised according to relevance, strengths and weaknesses. The study therefore gives good direction for further investigation on developing methods to deal with the discrepancies faced with autonomous mobile robot.

/pdf/a-review-on-challenges-of-autonomous-mobile-robot-and-sensor-yw1sv39uan.pdf

A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods

In free viewpoint television or 3D video, depth image based rendering (DIBR) is used to generate virtual views based on a textured image and its associated depth information. In doing so, image regions which are occluded in the original view may become visible in the virtual image. One of the main challenges in DIBR is to extrapolate known textures into the disoccluded area without inserting subjective annoyance. In this paper, a new hole filling approach for DIBR using texture synthesis is presented. Initially, the depth map in the virtual view is filled at disoccluded locations. Then, in the textured image, holes of limited spatial extent are closed by solving Laplace equations. Larger disoccluded regions are initialized via median filtering and subsequently refined by patch-based texture synthesis. Experimental results show that the proposed approach provides improved rendering results in comparison to the latest MPEG view synthesis reference software (VSRS) version 3.6 [1].

Depth image based rendering with advanced texture synthesis

A depth image-based rendering (DIBR) approach with advanced inpainting methods is presented. The DIBR algorithm can be used in 3-D video applications to synthesize a number of different perspectives of the same scene, e.g., from a multiview-video-plus-depth (MVD) representation. This MVD format consists of video and depth sequences for a limited number of original camera views of the same natural scene. Here, DIBR methods allow the computation of additional new views. An inherent problem of the view synthesis concept is the fact that image information which is occluded in the original views may become visible, especially in extrapolated views beyond the viewing range of the original cameras. The presented algorithm synthesizes these occluded textures. The synthesizer achieves visually satisfying results by taking spatial and temporal consistency measures into account. Detailed experiments show significant objective and subjective gains of the proposed method in comparison to the state-of-the-art methods.

/pdf/depth-image-based-rendering-with-advanced-texture-synthesis-3nnyv3xblx.pdf

Depth Image-Based Rendering With Advanced Texture Synthesis for 3-D Video

Depth Image Based Rendering (DIBR) technique has been recognized as a promising tool for supporting advanced 3D video services required in MultiView Video (MVV) systems. However, an inherent problem with DIBR is to fill newly exposed areas (holes) caused by disocclusions. This paper addresses the disocclusion problem. To deal with small disocclusions, hole-filling strategies have been designed by the state-of-the-art through pre-processing techniques of the depth video. For larger disocclusions, where depth pre-processing has some limitations, we propose an inpainting approach to retrieve missing pixels. Specifically, we propose in the texture and structure propagation process to take into account the depth information by distinguishing foreground and background parts of the scene. Experimental results illustrate the efficiency of the proposed method.

Depth-aided image inpainting for novel view synthesis

In this paper, a new algorithm is developed for recovering the large disocclusion regions in depth image based rendering (DIBR) systems on 3DTV. For the DIBR systems, undesirable artifacts occur in the disocclusion regions by using the conventional view synthesis techniques especially with large baseline. Three techniques are proposed to improve the view synthesis results. The first is the preprocessing of the depth image by using the bilateral filter, which helps to sharpen the discontinuous depth changes as well as to smooth the neighboring depth of similar color, thus restraining noises from appearing on the warped images. Secondly, on the warped image of a new viewpoint, we fill the disocclusion regions on the depth image with the background depth levels to preserve the depth structure. For the color image, we propose the depth-guided exemplar-based image inpainting that combines the structural strengths of the color gradient to preserve the image structure in the restored regions. Finally, a trilateral filter, which simultaneous combines the spatial location, the color intensity, and the depth information to determine the weighting, is applied to enhance the image synthesis results. Experimental results are shown to demonstrate the superior performance of the proposed novel view synthesis algorithm compared to the traditional methods.

/pdf/improved-novel-view-synthesis-from-depth-image-with-large-zi07h6l3q4.pdf

Improved novel view synthesis from depth image with large baseline

In this paper, we propose a novel algorithm to generate multiple virtual views from a video-plus-depth sequence for modern autostereoscopic displays. To synthesize realistic content in the disocclusion regions at the virtual views is the main challenging problem for this task. Spatial coherence and temporal consistency are the two key factors to produce perceptually satisfactory virtual images. The proposed algorithm employs the spatio-temporal consistency constraint to handle the uncertain pixels in the disocclusion regions. On the one hand, regarding the spatial coherence, we incorporate the intensity gradient strength with the depth information to determine the filling priority for inpainting the disocclusion regions, so that the continuity of image structures can be preserved. On the other hand, the temporal consistency is enforced by estimating the intensities in the disocclusion regions across the adjacent frames with an optimization process. We propose an iterative re-weighted framework to jointly consider intensity and depth consistency in the adjacent frames, which not only imposes temporal consistency but also reduces noise disturbance. Finally, for accelerating the multi-view synthesis process, we apply the proposed view synthesis algorithm to generate the intensity and depth maps at the leftmost and rightmost viewpoints, so that the intermediate views are efficiently interpolated through image warping according to the associated depth maps between the two synthesized images and their corresponding symmetric depths. In the experimental validation, we perform quantitative evaluation on synthetic data as well as subjective assessment on real video data with comparison to some representative methods to demonstrate the superior performance of the proposed algorithm.

Spatio-Temporally Consistent Novel View Synthesis Algorithm From Video-Plus-Depth Sequences for Autostereoscopic Displays

A consensus sampling technique for fast and robust model fitting

We present an integrated system for reconstruction an individualized 3D head model from a video sequence. Our reconstruction algorithm is based on the adaptation of a generic 3D head model. 3D geometric constraints on the head model are computed from the robust bundle adjustment algorithm and the structure from silhouette method. These 3D constraints are integrated to adapt the generic head model via radial basis function interpolation. Then the texture map of the reconstructed 3D head model is obtained by integrating all the images in the sequence through appropriate weighting. The proposed face model reconstruction method has the advantages of efficient computation as well as robustness against noises and outliers.

An integrated approach to 3D face model reconstruction from video

Systems and methods for obtaining camera parameters from images are provided. First, a sequence of original images associated with a target object under circular motion is obtained. Then, a background image and a foreground image corresponding to the target object within each original image are segmented. Next, shadow detection is performed for the target object within each original image. A first threshold and a second threshold are respectively determined according to the corresponding background and foreground images. Each original image, the corresponding background image, the first and second threshold are used for obtaining silhouette data and feature information associated with the target object within each original image. At least one camera parameter is obtained based on the entire feature information and the geometry of circular motion.

Chia-Ming Cheng

Papers

Improved novel view synthesis from depth image with large baseline

Spatio-Temporally Consistent Novel View Synthesis Algorithm From Video-Plus-Depth Sequences for Autostereoscopic Displays

A consensus sampling technique for fast and robust model fitting

An integrated approach to 3D face model reconstruction from video

System and method for obtaining camera parameters from multiple images and computer program products thereof