2010. 7. 31. 10:32 Architecture/Object Search
'전체 글'에 해당되는 글 120건
- 2010.07.31 Affine SIFT(Scale-Invariant Feature Transform)
- 2010.07.31 클레이 셔키: 인지 잉여는 어떻게 세상을 변화시킬 것인가
- 2010.07.30 Microsoft Research Street Slide View
- 2010.07.28 Interest Seam Image
- 2010.07.21 마가렛 골드 스테워트 : 유투브는 저작권에 대하여 어떻게 생각하는가
- 2010.06.19 SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding,
- 2010.06.18 Faster-than-SIFT Object Detection
- 2010.06.09 요즘의 나....
ICASSP09_ASIFT_final.pdf
ASIFT_png.tar.gz2010. 7. 31. 10:24 Idea Note/TED
클레이 셔키: 인지 잉여는 어떻게 세상을 변화시킬 것인가
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| 마이클 셔머: 자기 기만의 패턴 (0) | 2010.08.01 |
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2010. 7. 30. 14:30 Paper Reading/CVPR
Microsoft Research Street Slide View
Paper
http://research.microsoft.com/en-us/um/people/kopf/street_slide/paper/street_slide.pdf
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2010. 7. 28. 16:04 Paper Reading/CVPR
Interest Seam Image
We propose interest seam image, an efficient visual synopsis for video. To extract an interest seam image, a spatiotemporal energy map is constructed for the target video shot. Then an optimal seam which encompasses the highest energy is identified by an efficient dynamic programming algorithm. The optimal seam is used to extract a seam of pixels from each video frame to form one column of an image, based on which an interest seam image is finally composited. The interest seam image is efficient both in terms of computation and memory cost. Therefore it is able to power a wide variety of web-scale video content analysis applications, such as near duplicate video clip search, video genre recognition and classification, as well as video clustering, etc.. The representation capacity of the proposed interest seam image is demonstrated in a large scale video retrieval task. Its advantages are clearly exhibited when compared with previous works, as reported in our experiments.
[Reference]
http://videolectures.net/cvpr2010_hua_isi/'Paper Reading > CVPR' 카테고리의 다른 글
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2010. 7. 21. 16:39 Idea Note/TED
마가렛 골드 스테워트 : 유투브는 저작권에 대하여 어떻게 생각하는가
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| 클레이 셔키: 어떻게 소셜 미디어는 역사를 만들어내는가 (0) | 2010.05.30 |
| 데이빗 포그의 "단순함이 통한다" (0) | 2010.05.24 |
| 아도라 스비탁 (똑): 어른들이 어린이에게서 배울만한 것들 (0) | 2010.05.21 |
2010. 6. 19. 17:06 Paper Reading/CVPR
SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding,
Ruei-Sung Lin, David Ross, Jay Yagnik. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
http://www.cs.toronto.edu/~dross/LinRossYagnik_CVPR2010.pdf
Abstract:
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem . This paper presents a novel and fast algorithm for learning binary hash functions for fast nearest neighbor retrieval. The nearest neighbors are defined according to the semantic similarity between the objects. Our method uses the information of these semantic similarities and learns a hash function with binary code such that only objects with high similarity have small Hamming distance. The hash function is incrementally trained one bit at a time, and as bits are added to the hash code Hamming distances between dissimilar objects increase. We further link our method to the idea of maximizing conditional entropy among pair of bits and derive an extremely efficient linear time hash learning algorithm. Experiments on similar image retrieval and celebrity face recognition show that our method produces apparent improvement in performance over some state-of-the-art methods.
http://www.cs
Abstract:
Se
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2010. 6. 18. 21:47 Paper Reading/CVPR
Faster-than-SIFT Object Detection
Borja Peleato and Matt Jones
peleato@stanford.edu, mkjones@cs.stanford.edu
March 14, 2009
We propose the use of generic trees for realtime object search, and improve on the classication time taken by SIFT approximately by a factor of 5. Our approach also supports very fast training, taking no longer than it takes to search for an object in one candidate image.
Section 2 provides the background and an overview of the previous related work.
Section 3 explains in detail our proposed scheme,
before going into the analysis and results in section 4.
Finally, section 5 reviews the main features of our method and gives some possible directions for future work.
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2010. 6. 9. 23:00 Aphorism/Diary
