Sökning: "video object segmentation"
Visar resultat 1 - 5 av 11 avhandlingar innehållade orden video object segmentation.
1. Learning Representations for Segmentation and Registration
Sammanfattning : In computer vision, the aim is to model and extract high-level information from visual sensor measurements such as images, videos and 3D points. Since visual data is often high-dimensional, noisy and irregular, achieving robust data modeling is challenging. LÄS MER
2. Data-Efficient Learning of Semantic Segmentation
Sammanfattning : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. LÄS MER
3. Video Signal Processing: Compression Segmentation and Tracking
Sammanfattning : This thesis considers three separate research problems within the field of video processing.The first is concerned with segmenting an image, the second with tracking an object and the third with the communication of video across an unreliable network.Segmentation is an application-specific problem. LÄS MER
4. Enhancement of Salient Image Regions for Visual Object Detection
Sammanfattning : Salient object/region detection aims at finding interesting regions in images and videos, since such regions contain important information and easily attract human attention. The detected regions can be further used for more complicated computer vision applications such as object detection and recognition, image compression, content-based image editing, and image retrieval. LÄS MER
5. Reinforcement Learning for Active Visual Perception
Sammanfattning : Visual perception refers to automatically recognizing, detecting, or otherwise sensing the content of an image, video or scene. The most common contemporary approach to tackle a visual perception task is by training a deep neural network on a pre-existing dataset which provides examples of task success and failure, respectively. LÄS MER