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.