• Aucun résultat trouvé

Orientation covariant aggregation of local descriptors with embeddings

N/A
N/A
Protected

Academic year: 2021

Partager "Orientation covariant aggregation of local descriptors with embeddings"

Copied!
17
0
0

Texte intégral

Loading

Figure

Fig. 1. Similarities between regions of interest, based on SIFT kernel k (left), angle consistency kernel k θ (middle ) and both (right)
Fig. 2. Function k VM for different values of κ and its approximation ¯ k N VM using 1, 3 and 10 frequencies, as implicitly defined by the corresponding mapping α : [π, π] → R 2N+1 .
Fig. 3. Distribution of patch similarity for different values of orientation difference.
Figure 4 (left) shows the impact of these parameters on the performance. As to be expected, there is a trade-off between defining too narrow or too large
+3

Références

Documents relatifs

Third, Karkkainen’s approach (5) emphasized the knowledge-oriented integration of the customer direction, which is important for instance for engineer-to-order companies,

A data driven approach is based on reverse reinforcement learning, the objective of which is to learn the reward function from the behavioral observations of another (often human)

These methods are typically composed of an initial filtering stage where all database images are ranked in terms of similarity to a query image and a second re-ranking stage,

Web scale image retrieval using compact tensor aggregation of visual descriptors... Web scale image retrieval using compact tensor aggregation of

(2009) in their preface, wherein they hoped their book would “spark broader collaboration among sea-ice researchers to document and refine the best-practice approaches to

– Safety requirements have been considered for batch learning with MLPs and active learning with SVRs; it would be worth investigating whether active learning with MLPs and

The main goal of gamification is to increase the engagement of users by us- ing game-like techniques such as scoreboards and personalized fast feedback [7], making people feel

This paper 1 introduces an improved fusion of the object description based on the recent concept of generalized max- pooling and memory vectors, which summarizes a set of vec- tors by