Description: A disparity map is a visual representation that shows the difference in the location of the same point in 3D when viewed from different angles. This concept is fundamental in the field of computer vision, as it allows systems to interpret and understand the depth and three-dimensional structure of a scene from two-dimensional images. Disparity maps are generated from pairs of images taken from slightly different positions, similar to those captured by human eyes. By comparing these images, disparities can be calculated, which are the differences in the position of an object in the two images. This information is translated into a map that indicates the distance of each point in the scene from the camera. Disparity maps are essential for applications such as 3D reconstruction, autonomous navigation, and augmented reality, as they provide crucial data about the geometry of the environment. Additionally, their analysis allows for improved accuracy in tasks such as object segmentation and motion tracking, making them a valuable tool in the development of advanced technologies in computer vision.
Uses: Disparity maps are used in various computer vision applications, such as 3D reconstruction, where they allow for the creation of three-dimensional models from two-dimensional images. They are also fundamental in the autonomous navigation of vehicles, as they help detect obstacles and measure distances in the environment. In the realm of augmented reality, disparity maps enable the precise overlay of digital information onto the real world, enhancing user interaction. Additionally, they are used in object tracking systems and image segmentation, facilitating the identification and analysis of different elements within a scene.
Examples: A practical example of a disparity map can be found in stereoscopic vision systems used in autonomous vehicles, where cameras capture images from different angles and generate a map that helps identify the distance of objects on the road. Another example is in augmented reality applications, where disparity maps allow virtual elements to be realistically integrated into the physical environment, adjusting their position and scale according to the detected depth.
