Holoscopic 3D imaging and display technology: Camera/ processing/ display

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonHoloscopic 3D imaging “Integral imaging” was first proposed by Lippmann in 1908. It has become an attractive technique for creating full colour 3D scene that exists in space. It promotes a single camera aperture for recording spatial information of a real scene and it uses a regularly spaced microlens arrays to simulate the principle of Fly’s eye technique, which creates physical duplicates of light field “true 3D-imaging technique”. While stereoscopic and multiview 3D imaging systems which simulate human eye technique are widely available in the commercial market, holoscopic 3D imaging technology is still in the research phase. The aim of this research is to investigate spatial resolution of holoscopic 3D imaging and display technology, which includes holoscopic 3D camera, processing and display. Smart microlens array architecture is proposed that doubles spatial resolution of holoscopic 3D camera horizontally by trading horizontal and vertical resolutions. In particular, it overcomes unbalanced pixel aspect ratio of unidirectional holoscopic 3D images. In addition, omnidirectional holoscopic 3D computer graphics rendering techniques are proposed that simplify the rendering complexity and facilitate holoscopic 3D content generation. Holoscopic 3D image stitching algorithm is proposed that widens overall viewing angle of holoscopic 3D camera aperture and pre-processing of holoscopic 3D image filters are proposed for spatial data alignment and 3D image data processing. In addition, Dynamic hyperlinker tool is developed that offers interactive holoscopic 3D video content search-ability and browse-ability. Novel pixel mapping techniques are proposed that improves spatial resolution and visual definition in space. For instance, 4D-DSPM enhances 3D pixels per inch from 44 3D-PPIs to 176 3D-PPIs horizontally and achieves spatial resolution of 1365 × 384 3D-Pixels whereas the traditional spatial resolution is 341 × 1536 3D-Pixels. In addition distributed pixel mapping is proposed that improves quality of holoscopic 3D scene in space by creating RGB-colour channel elemental images

Innovative 3D Depth Map Generation From A Holoscopic 3D Image Based on Graph Cut Technique

Holoscopic 3D imaging is a promising technique for capturing full-colour spatial 3D images using a single aperture holoscopic 3D camera. It mimics fly’s eye technique with a microlens array, which views the scene at a slightly different angle to its adjacent lens that records three-dimensional information onto a two-dimensional surface. This paper proposes a method of depth map generation from a holoscopic 3D image based on graph cut technique. The principal objective of this study is to estimate the depth information presented in a holoscopic 3D image with high precision. As such, depth map extraction is measured from a single still holoscopic 3D image which consists of multiple viewpoint images. The viewpoints are extracted and utilised for disparity calculation via disparity space image technique and pixels displacement is measured with sub-pixel accuracy to overcome the issue of the narrow baseline between the viewpoint images for stereo matching. In addition, cost aggregation is used to correlate the matching costs within a particular neighbouring region using sum of absolute difference (SAD) combined with gradient-based metric and “winner takes all” algorithm is employed to select the minimum elements in the array as optimal disparity value. Finally, the optimal depth map is obtained using graph cut technique. The proposed method extends the utilisation of holoscopic 3D imaging system and enables the expansion of the technology for various applications of autonomous robotics, medical, inspection, AR/VR, security and entertainment where 3D depth sensing and measurement are a concern

Digital Refocusing: All-in-Focus Image Rendering Based on Holoscopic 3D Camera

This paper presents an innovative method for digital refocusing of different point in space after capturing and also extracts all-in-focus image. The proposed method extracts all-in-focus image using Michelson contrast formula hence, it helps in calculating the coordinates of the 3D object location. With light field integral camera setup the scene to capture the objects precisely positioned in a measurable distance from the camera therefore, it helps in refocusing process to return the original location where the object is focused; else it will be blurred with less contrast. The highest contrast values at different points in space can return the focused points where the objects are initially positioned as a result; all-in-focus image can also be obtained. Detailed experiments are conducted to demonstrate the credibility of proposed method with results

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine