Small Object Detection for Near Real-Time Egocentric Perception in a Manual Assembly Scenario
Detecting small objects in video streams of head-worn augmented reality devices in near real-time is a huge challenge: training data is typically scarce, the input video stream can be of limited quality, and small objects are notoriously hard to detect. In industrial scenarios, however, it is often possible to leverage contextual knowledge for the detection of small objects. Furthermore, CAD data of objects are typically available and can be used to generate synthetic training data. We describe a near real-time small object detection pipeline for egocentric perception in a manual assembly scenario: We generate a training data set based on CAD data and realistic backgrounds in Unity. We then train a YOLOv4 model for a two-stage detection process: First, the context is recognized, then the small object of interest is detected. We evaluate our pipeline on the augmented reality device Microsoft Hololens 2.
Code (0)
등록된 구현이 없습니다.
Tasks
object-detectionObject DetectionSmall Object DetectionUnityMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Analysis of voxel-based 3D object detection methods efficiency for real-time embedded systems
Real-time detection of objects in the 3D scene is one of the tasks an autonomous agent needs to perform for understanding its surroundings. While recent Deep Learning-based solutions achieve satisfactory performance, the…
3D Object Detectionobject-detectionObject DetectionHierLight-YOLO: A Hierarchical and Lightweight Object Detection Network for UAV Photography
The real-time detection of small objects in complex scenes, such as the unmanned aerial vehicle (UAV) photography captured by drones, has dual challenges of detecting small targets (<32 pixels) and maintaining real-time …
Small Object DetectionNETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection
Due to the advantages of real-time detection and improved performance, single-shot detectors have gained great attention recently. To solve the complex scale variations, single-shot detectors make scale-aware predictions…
Objectobject-detectionObject DetectionSHOP: A Deep Learning Based Pipeline for near Real-Time Detection of Small Handheld Objects Present in Blurry Video
While prior works have investigated and developed computational models capable of object detection, models still struggle to reliably interpret images with motion blur and small objects. Moreover, none of these models ar…
Objectobject-detectionObject DetectionReal Time Multi-Class Object Detection and Recognition Using Vision Augmentation Algorithm
The aim of this research is to detect small objects with low resolution and noise. The existing real time object detection algorithm is based on the deep neural network of convolution need to perform multilevel convoluti…
object-detectionObject DetectionReal-Time Object Detection