KNN: K- Nearest Neighbors. 39. Bag of features for image ... 41. 4. Image classification: discriminative method and much more ⦠SVM, ⦠41. Bag of features for ...
Introduc)on: Image descriptors - Descriptor: a high level representation of an image or video.
- Descriptor: a vector
- Dense and sparse descriptors
- Useful for:
- geometric based matching
- image retrieval,
- object recognition and categorization,
- .... 3
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Color HS+V histogram
Histogram of oriented gradients (HOG)
HS
V
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Combining histograms
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Histogram of oriented gradients (HOG)
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LBP: local binary pattern
LBP: local binary pattern
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Haar Wavelets
Haar Wavelets
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Video based descriptors (HOG/HOF)
Bag of Words (bag of features models)
Origin 1: texture recogni)on
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Bag of Words (bag of features models)
Origin 1: texture recogni)on
Origin 2: text analysis (Frequency of words of a dic)onary, Salton & McGill (1983))
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Bag of Words (bag of features models)
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Bag of Words
Bag of Words
1. extract features
2. learn visual vocabulary
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Bag of Words
Bag of features for image classification
3. represent images by frequencies of « visual words » Given an image to classify: 1. Extract features 2. Quantize features using visual vocabulary 3. Represent images by frequencies of “visual words” 4. Estimate the class using a previously learn classifier (eg. SVM, KNN, AdaBoost,…)
Regular grid – Vogel & Schiele, 2003 – Fei-Fei & Perona, 2005 Interest point detector – Csurka et al. 2004 – Fei-Fei & Perona, 2005 – Sivic et al. 2005
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Bag of features for image classification
Bag of features for image classification
1. Feature extraction
1. Feature extraction
Slide credit: Josef Sivic T. Chateau
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Slide credit: Josef Sivic T. Chateau
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Bag of features for image classification
Bag of features for image classification
2. Learning the visual vocabulary
2. Learning the visual vocabulary
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Bag of features for image classification
Bag of features for image classification
2. Learning the visual vocabulary
2. Learning the visual vocabulary
K-Means Clustering
Slide credit: Josef Sivic T. Chateau
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The codebook is used for quantizing features – A vector quantizer takes a feature vector and maps it to the index of the nearest codevector in a codebook – Codebook = visual vocabulary – Codevector = visual word
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Bag of features for image classification
Bag of features for image classification 2. Learning the visual vocabulary exemple of visual vocabulary
2. Learning the visual vocabulary
The codebook is used for quantizing features – A vector quantizer takes a feature vector and maps it to the index of the nearest codevector in a codebook – Codebook = visual vocabulary – Codevector = visual word
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Bag of features for image classification
Bag of features for image classification
2. Learning the visual vocabulary exemple of visual words
2-class problem (whatever the number of classes, the problem can be ..... pipeline and streaming I/O. This solution offers continuous data processing. .... Descriptors technique: A comparative studyâ, Optics and Lasers in engineering 45, 2007,.
It has been shown that the SVM method provides very good results in many practical ... Where ak are positive scalars and the functions Φk represent a basis in the ... The error rate is shown in table 1; we have compared our descriptors to other.
query descriptors are selected depending on two parameters: â period p of chosen .... detection. In: Conf. on Storage and Retrieval for Media Databases. (2002).
1 Introduction. Chemical risk is relative to situations in which chemical products are ... (Tulechki and Tanguy, 2012), computing the ex- position to the risk (Marre et .... Science and Software Engineering, 2(6):282â292. I.H. Witten and E. Frank.
queries for selective spatio-temporal video retrieval. Other approaches exist and involve spatio-temporal points of interest. These specific points are used for ...
For teaser of Animation's serie, GUDULE (Ellipse Anime) >> 2003. - For film THE NEST (director: Florent Emilio Siri) >> 2001. - For film BROTHERHOOD OF ...
2. These formulas have another important nice property (which is not true for .... TypeMMotionMDescriptors (Rnd MD) are a second family of invariants (containing ..... Fourier series correspond to the circle group, Fourier transforms to the ... Here,
Some decisive features have been added to the OMax computer assisted improvisation system: one is a video interface, which makes the virtual clone of the.
Nov 20, 1999 - Male workers who earn more are less likely to change occupation or ...... between the early 1970s and late 1970s (from 15 to 20 percent) and then falls to 13 ..... Rosen, Sherwin (1972), âLearning and Experience in the Labor ...
kT. I м е. Q HfI,Xr R RK. The proof is obvious and left to the reader. 2All along the ...... Fifth Ann. Workshop Computational Learning theory, ACM Press, 1992, pp.
Master of Science in Engineering. (Electronic ... 2002/2004. Bachelor of Science in Electric and Electronic Systems ... Basic knowledge object Eiffel language.
leurs vacances. - J'ai développé son site web, son SGV, le logiciel back-end (serveur principal), et une application iOS utilisant HTML, CSS, jQuery, Ruby, et.
Main activity: related to security business consultancy, as cryptography, data ... ENGLISH: good level, Obtained the 'Certificate of Business English' from the ...
