An evaluation framework for auto-conversion of 2D to 3D video streaming using depth profile and pipelining technique in handheld cellular devices

The main objective of this paper is to propose a Reliable and Speedy Communication for Upstream Emergency (RESCUE) framework to create 3D remote sensing videos. The proposed framework uses low memory space on mobile devices with the help of efficient pipelining processes. Many methods for converting 2D videos to 3D have been proposed wherein developers convert high-quality 2D to 3D. We propose a method to apply the pre-classification process on either training on dataset or heuristics based on the quality of streaming attributes. The evaluation framework automatically changes remote sensing videos from 2D to 3D by using depth profile with method filter, segmentation and sharpening transformation of the videos. The traditional Hough transformation algorithm is not suitable for hardware implementation and saliency is based on the colour histogram to support slow motion object of frames which leads to inordinate delay in converting 2D to 3D. Therefore, the RESCUE framework, with its extended vanishing point and line algorithm, is applied to provide suitable solutions and overcome the drawbacks of existing techniques. The framework is a lightweight process when compared with JAVRAE, and it utilizes limited phone memory and consumes less processing time.