Change Their Perception RGB D for 3 D Modeling and Recognition
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![Figure 4. (a) The RGB-D mapping algorithm in Henry et al. [5], combines sparse feature matching and dense ICP matching in both frame-to-frame odometry and loop closure](https://thumb-ap.123doks.com/thumbv2/123dok/3123647.1728039/4.567.47.276.413.626/figure-algorithm-combines-feature-matching-matching-odometry-closure.webp)
![Figure 9. Object detection using RGB-D [16]. Based on the LINE model that optimizes template matching for modern CPU architectures, both textured and textureless objects can be detected in real time in highly cluttered scenes.](https://thumb-ap.123doks.com/thumbv2/123dok/3123647.1728039/8.567.47.274.51.294/detection-optimizes-template-matching-architectures-textureless-detected-cluttered.webp)
![Figure 10. The detection-based object labeling using RGB-D mapping, 2) detect possible objects in each RGB-D frame, 3) project detection scores from [12], consisting of four stages: 1) construct a 3-D scene multiple frames into the scene, and 4) enforce label consistency through a voxel MRF on the point cloud.](https://thumb-ap.123doks.com/thumbv2/123dok/3123647.1728039/9.567.173.521.56.176/detection-labeling-possible-detection-consisting-construct-multiple-consistency.webp)
![Figure 12. The LEGO Oasis demo using RGB-D recognition [21]. Near-real-time object recognition allows interesting human–computer interactions using an overhead projector: a LEGO fire truck putting out a virtual fire on a house.](https://thumb-ap.123doks.com/thumbv2/123dok/3123647.1728039/10.567.45.277.51.214/figure-recognition-recognition-interesting-computer-interactions-overhead-projector.webp)
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