Search results for: scene segmentation - Bridge of Knowledge

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Search results for: scene segmentation

Search results for: scene segmentation

  • Accelerating Video Frames Classification With Metric Based Scene Segmentation

    This paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...

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  • Scene Segmentation Basing on Color and Depth Images for Kinect Sensor

    Publication

    In this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...

  • Urban scene semantic segmentation using the U-Net model

    Publication

    - Year 2023

    Vision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...

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  • Autonomous pick-and-place system based on multiple 3Dsensors and deep learning

    Publication

    - Year 2022

    Grasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...

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  • Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning

    Publication

    - Year 2022

    Grasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...

    Full text to download in external service