397:
306:
386:
Krystian
Mikolajczyk and Cordelia Schmid "A performance evaluation of local descriptors", IEEE Transactions on Pattern Analysis and Machine Intelligence, 10, 27, pp 1615--1630, 2005.
98:
299:
292:
88:
83:
457:
146:
438:
385:
373:
365:
93:
355:
335:
237:
141:
462:
252:
221:
108:
342:. An intermediate vector is computed from 17 location and 16 orientation bins, for a total of 272-dimensions.
136:
343:
216:
103:
195:
431:
174:
126:
360:
280:
275:
242:
19:
211:
131:
424:
60:
40:
45:
346:(PCA) is then used to reduce the vector size to 128 (same size as SIFT descriptor vector).
8:
35:
270:
404:
327:
190:
74:
55:
331:
169:
155:
408:
117:
50:
26:
412:
451:
65:
261:
339:
396:
338:-like descriptor that considers more spatial regions for the
449:
432:
300:
324:Gradient Location and Orientation Histogram
439:
425:
307:
293:
450:
391:
369:– Local Energy-based Shape Histogram
458:Feature detection (computer vision)
374:Feature detection (computer vision)
13:
204:Affine invariant feature detection
14:
474:
356:Scale-invariant feature transform
142:Maximally stable extremal regions
99:Hessian feature strength measures
395:
1:
379:
344:Principal components analysis
137:Determinant of Hessian (DoH)
132:Difference of Gaussians (DoG)
411:. You can help Knowledge by
196:Generalized structure tensor
7:
349:
175:Generalized Hough transform
127:Laplacian of Gaussian (LoG)
10:
479:
390:
361:Speeded Up Robust Features
212:Affine shape adaptation
463:Computer science stubs
276:Implementation details
94:Level curve curvature
330:that can be used in
230:Feature description
271:Scale-space axioms
420:
419:
317:
316:
20:Feature detection
470:
441:
434:
427:
405:computer science
399:
392:
328:image descriptor
309:
302:
295:
191:Structure tensor
183:Structure tensor
75:Corner detection
16:
15:
478:
477:
473:
472:
471:
469:
468:
467:
448:
447:
446:
445:
382:
352:
334:tasks. It is a
332:computer vision
313:
170:Hough transform
162:Hough transform
156:Ridge detection
84:Harris operator
12:
11:
5:
476:
466:
465:
460:
444:
443:
436:
429:
421:
418:
417:
400:
389:
388:
381:
378:
377:
376:
371:
363:
358:
351:
348:
326:) is a robust
315:
314:
312:
311:
304:
297:
289:
286:
285:
284:
283:
278:
273:
265:
264:
258:
257:
256:
255:
250:
245:
240:
232:
231:
227:
226:
225:
224:
222:Hessian affine
219:
214:
206:
205:
201:
200:
199:
198:
193:
185:
184:
180:
179:
178:
177:
172:
164:
163:
159:
158:
152:
151:
150:
149:
144:
139:
134:
129:
121:
120:
118:Blob detection
114:
113:
112:
111:
106:
101:
96:
91:
89:Shi and Tomasi
86:
78:
77:
71:
70:
69:
68:
63:
58:
53:
48:
43:
38:
30:
29:
27:Edge detection
23:
22:
9:
6:
4:
3:
2:
475:
464:
461:
459:
456:
455:
453:
442:
437:
435:
430:
428:
423:
422:
416:
414:
410:
407:article is a
406:
401:
398:
394:
393:
387:
384:
383:
375:
372:
370:
368:
364:
362:
359:
357:
354:
353:
347:
345:
341:
337:
333:
329:
325:
321:
310:
305:
303:
298:
296:
291:
290:
288:
287:
282:
279:
277:
274:
272:
269:
268:
267:
266:
263:
260:
259:
254:
251:
249:
246:
244:
241:
239:
236:
235:
234:
233:
229:
228:
223:
220:
218:
217:Harris affine
215:
213:
210:
209:
208:
207:
203:
202:
197:
194:
192:
189:
188:
187:
186:
182:
181:
176:
173:
171:
168:
167:
166:
165:
161:
160:
157:
154:
153:
148:
145:
143:
140:
138:
135:
133:
130:
128:
125:
124:
123:
122:
119:
116:
115:
110:
107:
105:
102:
100:
97:
95:
92:
90:
87:
85:
82:
81:
80:
79:
76:
73:
72:
67:
66:Roberts cross
64:
62:
59:
57:
54:
52:
49:
47:
44:
42:
39:
37:
34:
33:
32:
31:
28:
25:
24:
21:
18:
17:
413:expanding it
402:
366:
323:
319:
318:
247:
46:Differential
262:Scale space
452:Categories
380:References
340:histograms
350:See also
281:Pyramids
61:Robinson
56:Prewitt
41:Deriche
403:This
104:SUSAN
51:Sobel
36:Canny
409:stub
367:LESH
336:SIFT
320:GLOH
248:GLOH
243:SURF
238:SIFT
147:PCBR
109:FAST
253:HOG
454::
440:e
433:t
426:v
415:.
322:(
308:e
301:t
294:v
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.