(a) (b) 1 beach 1 Tag Number of phogoraphs beach 2,488,923 sea 1,689,924 coastline 60,245 shoreline 47,114 2 Tag Average error [m] beach 7, sea
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1 DEIM Forum 2014 E4-1 Flickr / DC gs13008@s.inf.shizuoka.ac.jp, dgs11538@s.inf.shizuoka.ac.jp, ishikawa-hiroshi@sd.tmu.ac.jp, yokoyama@inf.shizuoka.ac.jp Flickr X X beach beach 80% 500m 1. GIS GPS Flickr [1] Panoramio [2] Flickr beach japan 2013 winter iphone canon bird tree 1 coast OpenStreetMap [7] NOAA [8] 2 Flickr 3 beach coast Flickr
2 (a) (b) 1 beach 1 Tag Number of phogoraphs beach 2,488,923 sea 1,689,924 coastline 60,245 shoreline 47,114 2 Tag Average error [m] beach 7, sea 8, shoreline 23, coastline 3, Tag < = 100m[ ] < = 500m[ ] beach sea coastline shoreline OpenStreetMap m 500m 2 m 3 500m 2 sea beach sea 500m GPS m 1, 2, 3 beach 1 beach 1 1(a) 1(b) 1(a) 1(a) 1(b) beach
3 右上の 25 は,35 から 3 へ引く 7 と 9 は 35 に隣接している 左下の25は,20から下へ引く 83は20と隣接しており 7 25, 6 15 残るは0なので,20から対称 ( 反対方向 ) へ引く 右下の22は周りに候補がないため 線を引かない 40 20右上の20は候補じゃない 右 左 (a) (b) (c) 2 3. beach Algorithm 1 θ num(cell) cell around4(cell) cell 4 around8(cell) cell 8 max(cells) cells opposite(cella,cellb) cella cellb center(cella,cellb) cella cellb 2(a) 1 1 Nm 1 θ 2(a) θ = Algorithm 1 1: arguments: θ 2: candidate cells φ 3: foreach cellα 4: foreach cellβ around4(cellα) 5: if num(cellα) num(cellβ) > θ then 6: candidate cells candidate cells cellα 7: end if 8: end foreach 9: end foreach 10: 11: foreach cellc candidate cells 12: count 0 13: foreach cella around8(cellc) 14: if is candidate cell(cella) then 15: count count : end if 17: end foreach 18: if count > 0 then 19: cellα max(around8(cellc)) 20: cellβ max(around8(cellc) cellα around4(cellα)) /* cellc 8 cella cella 5 */ 21: if num(cellβ) = 0 then 22: cellb opposite(cellc,cellα) 23: end if 24: drawline(center(cellc,cellα), center(cellc,cellβ)) 25: end if 26: end foreach (b) 2(c)
4 右上の 25 は候補でない差分が 20 でないため 左の 20 はつなぐ相手がないため削除 右上の 25 は候補でない差分が 20 でないため 左の 20 はつなぐ相手がないため削除 右 左 (a) (b) (c) 3 Algorithm 2 is exist point in cell(point,cell) cell point get side between cells(cella,cellb) cella cellb get points(side) side center(points) points Algorithm 2 1: foreach cellα 2: foreach pointα cellα 3: cells φ 4: foreach cella around(cellα) 5: if is exist point in cell(pointα,cella) then 6: cells cells cella 7: end if 8: end foreach 9: cellβ max(cells) 10: side get side between cells(cellα,cellβ) 11: points get points(side) 12: pointα center(points) 13: redrawline(cellα) /* pointα */ 14: end foreach 15: end foreach 16: 17: foreach lineα 18: delete(lineα) 19: end foreach 2 ( 2(b), 2(c)) (a) 3 3(b) 3(c) 3(b) Algorithm 3 (1) 1: arguments: maxdist 2: arguments: maxdel 3: arguments: disttable 4: sort order by distance ascending(disttable) 5: foreach row disttable 6: p1 get first point(row) 7: p2 get second point(row) 8: if not connect(p1) and not connect(p2) and get distance(row) < maxdist then 9: for 1 to maxdel do 10: if try connect(p1,p2) then 11: break 12: end if 13: tmp1 p1 14: p1 get connect point(get another point(p1)) 15: if try connect(p1,p2) then 16: break 17: end if 18: tmp2 p1 19: p1 tmp1 20: p2 get connect point(get another point(p2)) 21: if try connect(p1,p2) then 22: break 23: end if 24: p1 tmp2 25: end for 26: end if 27: end foreach
5 Algorithm 3, Algorithm 4 Algorithm 4 (2) 1: declare function delete connect line (point) 2: while is exist(point) do 3: tmp get connect point(get another point(point) 4: delete (get line(point)) 5: point tmp 6: end while 7: end function 8: 9: declare function try connect (p1,p2) 10: if aim to(p1,p2) and aim to(p2,p1) then 11: delete connect line(get connect point(p1)) 12: delete connect line(get connect point(p2)) 13: redrawline(p1,p2) 14: return true 15: end if 16: return false 17: end function 18: 19: declare function aim to (p1,p2) 20: result true 21: if left side(p1) and lon(p1) < lon(p2) then 22: result false 23: end if 24: if right side(p1) and lon(p1) > lon(p2) then 25: result false 26: end if 27: if top side(p1) and lat(p1) > lat(p2) then 28: result false 29: end if 30: if bottom side(p1) and lat(p1) < lat(p2) then 31: result false 32: end if 33: return result 34: end function maxdist maxdel disttable get first point(row) row get second point(row) get first point row get distance(row) row not connect(point) point get connect point(point) point get another point(point) point left side(point) point right side(point) point top side(point) point bottom side(point) point get line(point) point lon(point) point lat(point) point maxdist maxdel 4. Flickr OpenLayers [3] beach 12, ,566 GPS θ 15 maxdist 5 maxdel 5 4(a) 4(b) 2 N 1 5
6 (a) 分割したグリッド (b) 本手法で描いた海岸線 図 4 ハワイのマウイ島の写真を用いた海岸線の描画結果 (a) 分割したグリッド (グリッドサイズ大) (b) 本手法で描いた海岸線 (グリッドサイズ大) (c) 分割したグリッド (グリッドサイズ小) (d) 本手法で描いた海岸線 (グリッドサイズ小) 図 5 イギリス写真を用いた海岸線の描画結果 用いた 図 5(a) は 分割したグリッドの位置 図 5(b) は 描 やブリストル海峡のような細かい凹凸部分も再現出来ている いた海岸線を表している ハワイ同様に 概ねの海岸線が描け しかし 南西の端のペンザンス付近は 線が途切れて島のよう ているが 内陸部にも線が存在する また 線が交差している に表示されている 場所が存在する これは 離れたセルのつなげる際に線端の向 内陸部の線が存在しない理由は次のように考えられる グ きだけを利用しており つなぐ候補となる 2 点が向い合ってい リッドサイズが大きい場合は 多少写真が散らばっていても 1 れば その 2 点間に線があるかどうかを考慮していないためで つのセルにまとめられるが グリッドサイズが小さい場合は ある これについては 今後の課題とする 写真が複数のセルに散らばり 写真枚数が少ない地域は線を引 図 5(c) 図 5(d) は 図 5(a) 図 5(b) のグリッドサイズを小 く候補となる可能性が低い また ノイズとなる写真 (e.g., 内 さくしたものである 図 5(d) と図 5(b) を比較すると 図 5(d) 陸部で撮影された beach と関係のない写真に beach とタグ では 図 5(b) に存在した内陸部の線が存在しない また グ 付けされた写真) の撮影位置は 海岸付近で撮影された写真に リッドのサイズが小さいため ウェーマス付近のポートランド 比べると線状にはなっていないと考えられる そのため 内陸
7 4 4(b) Distance Number of lines 0m 250m 40 (69 ) 250m 500m 4 (7 ) 500m 750m 7 (12 ) 750m 1km 2 (3 ) 1km 5 (9 ) 5 5(b) Distance Number of lines 0m 250m 112 (59 ) 250m 500m 10 (5 ) 500m 750m 9 (5 ) 750m 1km 4 (2 ) 1km 55 (29 ) 6 5(d) Distance Number of lines 0m 250m 174 (73 ) 250m 500m 22 (9 ) 500m 750m 14 (6 ) 750m 1km 10 (4 ) 1km 20 (8 ) 5(b) 5. OpenStreetMap (b) 5(b) 5(d) m 250m 250m 1km 2 beach 500m 80 1km 5 5(b) 6. Thomee [5] Thomee Scale-space theory 1 Zhang [4] Shirai [6] Zhang Shirai 7. beach beach [1] Flickr, [2] Panoramio, [3] OpenLayers, [4] Haipeng Zhang, Mohammed Korayem and David J. Crandall, Mining Photo-sharing Websites to Study Ecological Phenomena, Proceedings of the 21th international conference on World wide web, Pages , 2012 [5] Bart Thomee and Adam Rae, Uncovering Locally Characterizing Regions within Geotagged Data, Proceedings of the 22th international conference on World wide web, 2013 [6] M. Shirai, M. Hirota, H. Ishikawa and S. Yokoyama, A method of area of interest and shooting spot detection using geo-tagged photographs, ACM SIGSPATIAL Workshop on Computational Models of Place 2013 at ACM SIGSPATIAL GIS 2013, Orlando USA, [7] OpenStreetMap Data, [8] NOAA National Geophysical Data Center,
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