2D-3D Conversion from a single camera by using relative depth estimation and occlusion detection (Ref.TEC0071)

In the context of computer vision, the monocular depth estimation problem can be defined as inferring the depth order of the objects present in a scene using only information from a single camera (an image or a video sequence). 

The technology allows to extract depth information at low-level, so that no knowledge or understanding on the image content is required.  It is based on a mathematical model that encodes, in a quantitative manner, perceptual depth cues at different scales such as convexity/concavity, inclusion, and T-junctions, leading to an interpretation that is consistent with the perception of the human visual system. The model can be easily interpreted and tuned according to a specified visual response.

·       Accurate, robust to noise, and temporally consistent dense maps of relative depth, while not compromising the performance of the whole system.

·       Efficient (pyramidal) implementation, easy video extension, simple configuration, and fast performance.

·       Significantly outperforming state-of-the-art approaches in accuracy and efficiency.

Market ooportunities in high level applications in media, entertainment, security, telecommunications: object detection and recognition, conversion of 2D video content to 3D, multi-camera view generation or interpolation, video editing, advertisement insertion in video content, or seamless visual effects.

2D-3D Conversion from a single camera by using relative depth estimation and occlusion detection
Ref: 
TEC-0071/P-0023