Tutorial Visual Perception 1 Towards Computer Vision 2

Tutorial Visual Perception 1. Towards Computer Vision 2. Steps in 3 D Object Modelling 3. Camera Modelling and Calibration 4. Stereo. Vision & Epipolar Geometry 5. Fundamental Matrix Estimation 6. Coded Structured Light

Human Vision: • Identify objects • Locate its 3 D position. Image acquisition Image interpretation

The Human Eye ? Eye shape: • Cornea: Transparent surface. • Sclera: Outer cover composed of a fibrous coat that surrounds the choroid. • Choroid: a layer of blood capillaries. • Retina: layer inside the choroid composed of two types of receptors (rods and cones) and a netword of nerves. • Optic nerve: Retinal nerves leave the eye to the brain trough the optic nerve bundle. Image enhancement: • Cornea: Transparent surface. • Lens: Focuses the light to the retina surface to perform proper focus of near and distant objects. • Iris: Acts as a diaphragm to control the amount of light entering the eye.

How an eye is working ? Image acquisition: • Retina: Composed of • 100 M. Rods: Long slender receptors. Sensitive at low levels of light. • 6. 5 M. Cones. Shorter and thicker receptors. Sensitive at high levels of light. Greatest presence at the Fovea region (sharpest vision). • Three types of cones with different wavelength absorption with peaks in the blue, green and red light spectrum • Light stimulus activate a rod or cone producing a nerve impulse which is transmitted through the optic nerve. More information at: http: //www. vision. ca/eye/lobby. html

Image acquisition Computer Vision: Object Recognition. Object Localisation. Advantage: Automatisation. Constraint: Difficult to transmit the human intelligence and skills to a computer. Image interpretation Applications: Shape Inspection for quality control Rapid Prototyping Computer assisted surgery Film making effects Object picking Robot Navigation

3 D Information System selection Modelling Calibration Correspondence Get 3 D Cloud Data Fusion

System Selection Combination of computational and optical techniques aimed at estimating or making explicit geometric (3 D shape) properties of objects or scenes from their digital images. • stereovision • pattern projection • laser scanning • shape from X (motion, texture, shading, focus, zoom) Computation for all or some pixels of the distance between a known reference frame and the scene point that is imaged in those pixels. The output is a range image (depth map) or a cloud of points {(xi, yi, zi), i=1. . N}. The fusion of several range images or point clouds corresponding to partially different views of an object may yield its full 3 D digitization.

Main processes in 3 D digitization graphic surface object Range sensing N 3 D point clouds Geometric fusion solid (triangles) Object modeling solid (splines) best next view Sensor planning System Selection • Stereovision • Pattern projection • Laser scanning • Shape from X (motion, texture, shading, focus, zoom) Texture mapping coloured solid

Geometric fusion 24 aligned 3 D scans ready for merging set of six 3 D scans acquired from different viewpoints and their alignment (center) 24 meshes merged into a surface triangulation.

Applications – Dense reconstruction – Visual inspection – Object localization – Camera localization HT RT C CT W P H WT R