This paper shows how stereo and Time-of-Flight (ToF) images can be combined to estimate dense depth maps in order to automate plant phenotyping. We focus on some challenging plant images captured in a glasshouse environment, and show that even the state-of-the-art stereo methods produce unsatisfactory results. By developing a geometric approach which transforms depth information in a ToF image to a localised search range for dense stereo, a global optimisation strategy is adopted for producing smooth and discontinuity-preserving results. Since pixel-by-pixel depth data are unavailable for our images and many other applications, a quantitative method accounting for the surface smoothness and the edge sharpness to evaluate estimation results is proposed. We compare our method with and without ToF against other state-of-the-art stereo methods, and demonstrate that combining stereo and ToF images gives superior results.
|Title of host publication||17th Scandinavian Conference on Image Analysis, SCIA 2011, Ystad, Sweden, 23 - 27 May, 2011|
|Publication status||Published - 2011|
|Event||17th Scandinavian Conference on Image Analysis, SCIA 2011, Ystad, Sweden - |
Duration: 23 May 2011 → 27 May 2011
|Conference||17th Scandinavian Conference on Image Analysis, SCIA 2011, Ystad, Sweden|
|Period||23/05/11 → 27/05/11|