• Aucun résultat trouvé

VIMANCO: Vision manipulation of non-cooperative objects

N/A
N/A
Protected

Academic year: 2021

Partager "VIMANCO: Vision manipulation of non-cooperative objects"

Copied!
9
0
0

Texte intégral

Loading

Figure

Figure 1: Examples of visual features used in visual servoing
Figure 2: a) For Vision Based Manipulation of a non-cooperative object three steps are required: object recognition,  object tracking and visual servoing  b) Global VIMANCO system architecture
Figure 3: a) Object Recognition s/s: Off-line training b) Object Recognition s/s: on-line object recognition  The input to the system consists of images of the object to be modelled
Figure 4: Features tracking in visual servoing experiments (ordered by subjective increasing difficulties) (a) tracking  fiducial markers (b) tracking contours (c) 3D model-based tracking within “clean” environment (d) 3D model-based
+3

Références

Documents relatifs

It may be the subject or the direct object in a sentence and thus, can mean either 'who?' or 'whom?' You may also choose to use the longer forms: qui est-ce qui to ask 'who?', qui

Basically, in the first case, for each frame, the objects are detected and then associated (using a data association algo- rithm) to the previously tracked objects that are the

Our cooperation method is based on particle filter- ing, running in a cooperative way on both visible and infrared sequences: if a difficulty arises in one of the modality,

We expected that if information in peripheral vision is used to generate a predictive signal that shapes visual processing in central vision, the peripheral influence on

The basic motivation for CellStore project was development of an experimental database, which can be used as a basis for experimenting with various database algorithms like locking

In this paper we explore this technique for on-line multi-object tracking through a simple tracking- by-detection scheme, with background subtraction for object detection and

Isabelle Leang graduated from the Ecole Nationale Supérieure de l’Electronique et de ses Applications (France), received a Master degree in Computer Sciences from the Université

We present an algorithm that accurately tracks the pose of a complex object. We provide validation on both simulated and real data. The proposed approach outperforms one of the