This is a video demonstrating the depth estimation algorithm created at ETRO-VUB. The algorithm processes raw data of the Silicam in real-time and drives a cuboid-based 3D visualization. A live demo presentation of the system is planned at ACM/IEEE International conference on Distributed Smart Cameras (ICDSC 2013) ([ Ссылка ]), entitled "Demo: Depth Estimation for 1K-Pixel Stereo Visual Sensors" by Jan Hanca, Frederik Verbist, Nikos Deligianis, Richard Kleihorst, and Adrian Munteanu.
The abstract of the paper can be found below:
This demonstrator explores the applicability of depth estimation based on stereo video with extremely low resolution, i.e., 30x30 pixels. To handle this resolution, a disparity estimation technique, composed of local correlation-based matching of two low-resolution stereo images followed by segmentation driven post-processing, is proposed. The demonstrator includes a setup where a stereo visual sensor is connected to a laptop computer, running the proposed depth estimation method in real-time and displaying the resulting disparity maps. In addition, an interface is available to give the user control over the proposed algorithm parameters. To illustrate the superior performance, the results of proposed method can be readily compared to disparity maps generated using a typical global correlation-based depth estimation algorithm.
