• Tidak ada hasil yang ditemukan

isprsannals II 3 W5 393 2015

N/A
N/A
Protected

Academic year: 2017

Membagikan "isprsannals II 3 W5 393 2015"

Copied!
8
0
0

Teks penuh

Loading

Gambar

Figure 1: The proposed building detection technique.
Figure 2: Separating nearby buildings: (a) input (non-ground)point cloud data, (b) extracted building footprint (buildings aremerged), (c) corresponding building mask, (d) boundaries of twoneighbouring roof planes, (e) close segments of plane boundaries(dashed line to test gap between planes) and (f) improved buildingfootprints (buildings are separated).
Figure 3: Change detection: (a) existing building map, (b) extracted buildings from new data, (c) mask from (a) & (b) showing old, newand existing building/parts, (d) mask for old building parts only, (e) morphological opening of (d), (f) estimation of length and width ofa component in (e) or (h), (g) mask for new building parts only, (h) morphological opening of (g), (i) final change detection results.
Table 1: Four test data sets, each from two dates: dimensions inmetres, point density in points/mbuildings within 10 m2, B size indicates the number of2, 25 m2 and 50 m2 in area, respectively.
+4

Referensi

Dokumen terkait

Buildings are usually characterized by vertical walls that define the footprint of each building and can be reconstructed using image matching on oblique

Sec- ond, the rainfall data measured by the municipality stations are used as ground-truth to validate the values approximated from the ARPAL data set: in this setting,

Result at the system level Overall, we load several billion points into the point cloud server, perform several processing in and out of base ( s to hour), extensively use simple

Abnormal activities of Jaywalking are successfully detected as shown in Figure 4(b) and (c). The principle for this detection is also because of the percentage of the

The SPR process determines the extrinsic camera parameters such as the position and attitude at the acquisition time of an image using the ground control points (GCP).. Since

Another approach similar to this has been proposed which does not need the clutter ground truth labels (Wang et al., 2010).. In this paper, we tackle the problem of indoor

c) the matched candidate points.. Examples of reconstructed objects, a) for toeboard. In Figure 14a, the green points are original points of the divided building façade, while

On the other hand, the problem of extracting a DTM from laser scanning is widely studied, the main challenges being the registration of overlapping strips, the filter- ing of ground