Sökning: "Object Classification"

Visar resultat 1 - 5 av 79 avhandlingar innehållade orden Object Classification.

1. 1. Components of Embodied Visual Object Recognition : Object Perception and Learning on a Robotic Platform

   Författare :Marcus Wallenberg; Per-Erik Forssén; Mårten Björkman; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; computer vision; object recognition; stereo vision; classification;

   Sammanfattning : Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. LÄS MER

3. 2. Studies in Semantic Modeling of Real-World Objects using Perceptual Anchoring

   Författare :Andreas Persson; Amy Loutfi; Alessandro Saffiotti; Severin Lemaignan; Örebro universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Perceptual Anchoring; Semantic World Modeling; Sensor-Driven Acquisition of Data; Object Recognition; Object Classification; Symbol Grounding; Probabilistic Object Tracking;

   Sammanfattning : Autonomous agents, situated in real-world scenarios, need to maintain consonance between the perceived world (through sensory capabilities) and their internal representation of the world in the form of symbolic knowledge. An approach for modeling such representations of objects is through the concept of perceptual anchoring, which, by definition, handles the problem of creating and maintaining, in time and space, the correspondence between symbols and sensor data that refer to the same physical object in the external world. LÄS MER

4. 3. Visual Object Tracking and Classification Using Multiple Sensor Measurements

   Författare :Yixiao Yun; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; sensor fusion; Riemannian manifold; visual pattern classification; multiple view geometry; Visual object tracking; boosting; multiple sensor measurement;

   Sammanfattning : Multiple sensor measurement has gained in popularity for computer vision tasks such as visual object tracking and visual pattern classification. The main idea is that multiple sensors may provide rich and redundant information, due to wide spatial or frequency coverage of the scene, which is advantageous over single sensor measurement in learning object model/feature and inferring target state/attribute in complex scenarios. LÄS MER

5. 4. Exploring Biologically-Inspired Interactive Networks for Object Recognition

   Författare :Mohammad Saifullah; Arne Jönsson; Rita Kovordányi; Christian Balkenius; Linköpings universitet; []
   Nyckelord :Interactive neural networks; Biologically-Inspired models; Visual attention; Object recognition.; TECHNOLOGY; TEKNIKVETENSKAP;

   Sammanfattning : This thesis deals with biologically-inspired interactive neural networks for the task of object recognition. Such networks offer an interesting alternative approach to traditional image processing techniques. Although the networks are very powerful classification tools, they are difficult to handle due to their bidirectional interactivity. LÄS MER

7. 5. Object Classification and Image Labeling using RGB-Depth Information

   Författare :Mostafa Pordel; Thomas Hellström; Ulrik Söderström; Umeå universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

   Sammanfattning : This thesis is part of research for the vision systems of four robots in the EU funded project, CROPS[l], where the robots should harvest apples, sweet peppers and grapes, and explore forests. The whole process of designing such a system, including the software architecture, creation of the image database, image labeling and object detection, is presented. LÄS MER