Abstract: A 360-degree Virtual Reality Snap-On Camera that can be connected to any mobile device using the micro-USB, USB-C connector or Lightning connector along with the corresponding mobile application to capture 360-degree and Virtual Reality (VR) Videos is provided. The device consists of two or more cameras with a high-field of lenses connected through a microcontroller or microprocessor. The streams are interpreted, decoded and analyzed by the mobile application through the microcontroller or microprocessor, and mapped by inbuilt Graphics Processing Unit optimized stitching and blending method for a 360-degree VR video experience. The method can perform VR facial filters, VR Avatars and Augmented Reality spatial tracking over the VR Streams. The stream can be further compressed using optimized method for delivery over the cloud networks and can then be shared across social networks, live streamed and viewed either stand-alone or with a VR headset.

Abstract: In exemplary implementations of this invention, a light field camera uses a light field dictionary to reconstruct a 4D light field from a single photograph. The light field includes both angular and spatial information and has a spatial resolution equal to the spatial resolution of the imaging sensor. Light from a scene passes through a coded spatial light modulator (SLM) before reaching an imaging sensor. Computer processors reconstruct a light field. This reconstruction includes computing a sparse or compressible coefficient vector using a light field dictionary matrix. Each column vector of the dictionary matrix is a light field atom. These light field atoms each, respectively, comprise information about a small 4D region of a light field. Reconstruction quality may be improved by using an SLM that is as orthogonal as possible to the dictionary.

Abstract: In exemplary implementations of this invention, a light field camera uses a light field dictionary to reconstruct a 4D light field from a single photograph. The light field includes both angular and spatial information and has a spatial resolution equal to the spatial resolution of the imaging sensor. Light from a scene passes through a coded spatial light modulator (SLM) before reaching an imaging sensor. Computer processors reconstruct a light field. This reconstruction includes computing a sparse or compressible coefficient vector using a light field dictionary matrix. Each column vector of the dictionary matrix is a light field atom. These light field atoms each, respectively, comprise information about a small 4D region of a light field. Reconstruction quality may be improved by using an SLM that is as orthogonal as possible to the dictionary.