This paper proposes a technique for object recognition using superquadric built models. Superquadrics, which are three dimensional models suitable for part-level representation of objects, are reconstructed from range images using the recover-and-select paradigm. Using an interpretation three, the presence of an object in the scene from the model database can be hypothesized. These hypotheses are verified by projecting and re-fitting the object model to the range image which at the same time enables a better localization of the object in the scene
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
This work contributes to the robotic bin-picking problem, and more specifically to the problem of lo...
This proposal is concerned with three-dimensional object recognition from range data using superquad...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
We present a novel approach to reliable and efficient recovery of part-descriptions in terms of supe...
In this thesis methods needed to model 3D objects, segment them from 3D data, and track them through...
Object representation denotes representing three-dimensional (3D) real-world objects with known grap...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
Segmentation of range images using superquadric entities has been pointed out by a number of researc...
Centre for Intelligent Systems and their ApplicationsThis thesis addressed the problem of recognizin...
Volumetric part models play an important part in robotic applications such as grasping, path plannin...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
This work contributes to the robotic bin-picking problem, and more specifically to the problem of lo...
This proposal is concerned with three-dimensional object recognition from range data using superquad...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
This paper proposes a technique for object recognition using superquadric built models. Superquadric...
We present a novel approach to reliable and efficient recovery of part-descriptions in terms of supe...
In this thesis methods needed to model 3D objects, segment them from 3D data, and track them through...
Object representation denotes representing three-dimensional (3D) real-world objects with known grap...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
Undeformed superquadrics are volumetric modeling primitives with an extensive shape vocabulary that ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
Segmentation of range images using superquadric entities has been pointed out by a number of researc...
Centre for Intelligent Systems and their ApplicationsThis thesis addressed the problem of recognizin...
Volumetric part models play an important part in robotic applications such as grasping, path plannin...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
With the recent advancements in deep neural computation, we devise a method to recover superquadric ...
This work contributes to the robotic bin-picking problem, and more specifically to the problem of lo...
This proposal is concerned with three-dimensional object recognition from range data using superquad...