• 로봇학회논문지
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• 제19권1호
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• pp.130-138
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• 2024

High-precision 3D Object Detection is a crucial component within autonomous driving systems, with far-reaching implications for subsequent tasks like multi-object tracking and path planning. In this paper, we propose a novel approach designed to enhance the performance of 3D Object Detection, especially in heading angle estimation by employing a moving object segmentation technique. Our method starts with extracting point-wise moving labels via a process of moving object segmentation. Subsequently, these labels are integrated into the LiDAR Pointcloud data and integrated data is used as inputs for 3D Object Detection. We conducted an extensive evaluation of our approach using the KITTI-road dataset and achieved notably superior performance, particularly in terms of AOS, a pivotal metric for assessing the precision of 3D Object Detection. Our findings not only underscore the positive impact of our proposed method on the advancement of detection performance in lidar-based 3D Object Detection methods, but also suggest substantial potential in augmenting the overall perception task capabilities of autonomous driving systems.

• 로봇학회논문지
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• 제16권1호
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1434-1449
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• 2019

Video object segmentation is a significant task in computer vision, but its performance is not very satisfactory. A method of video object segmentation using weakly temporal information is presented in this paper. Motivated by the phenomenon in reality that the motion of the object is a continuous and smooth process and the appearance of the object does not change much between adjacent frames in the video sequences, we use a feed-forward architecture with motion estimation to predict the mask of the current frame. We extend an additional mask channel for the previous frame segmentation result. The mask of the previous frame is treated as the input of the expanded channel after processing, and then we extract the temporal feature of the object and fuse it with other feature maps to generate the final mask. In addition, we introduce multi-mask guidance to improve the stability of the model. Moreover, we enhance segmentation performance by further training with the masks already obtained. Experiments show that our method achieves competitive results on DAVIS-2016 on single object segmentation compared to some state-of-the-art algorithms.

• 방송공학회논문지
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• 제27권3호
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• pp.273-282
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• 2022

MPEG 내 VCM 그룹은 머신을 위한 비디오 코덱을 표준화하는 것으로 목표로 하고 있다. VCM 그룹은 객체 탐지, 객체 분할, 객체 추적 등 3가지의 머신비전 태스크를 포함한 데이터 세트와 데이터 세트 별 기준 데이터인 Anchor를 제공하고 있으며, 평가 템플릿을 이용하여 후보 기술군과 Anchor의 압축 대비 머신비전 성능을 비교할 수 있다. 하지만 성능 비교는 머신비전 태스크 별로 분리하여 수행되고 있으며, 다수의 머신비전 태스크에 대한 성능 평가를 수행할 수 있는 비트스트림을 생성할 수 있는 데이터는 별도로 제공하고 있지 않다. 본 논문에서는 인공 지능 기반 멀티 태스크를 위한 비디오 코덱의 성능 평가 방안에 대해 제안한다. 하나의 비트스트림의 크기 척도인 픽셀 당 비트수(BPP, Bits Per Pixel) 와 각 태스크의 정확도 결과인 Mean Average Precision(mAP)를 기반으로 산술 평균, 가중 평균, 조화 평균 등 총 3가지의 멀티 태스크 성능 평가 지표를 제안하며 mAP 결과를 기반으로 성능 결과를 비교하고자 한다. 멀티 태스크에서 태스크 별 mAP 결과 값의 범위의 차이가 있을 수 있으며 차이로 인해 생길 수 있는 성능 평가와 관련된 문제를 방지하고자 정규화한 mAP 기반 멀티 태스크 성능 결과를 산출하고 평가하고자 한다.

• International Journal of Precision Engineering and Manufacturing
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• 제5권1호
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• 로봇학회논문지
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• 제12권4호
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• pp.441-447
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• 2017

Robot arms are being increasingly used in various fields with special attention given to unmanned systems. In this research, we developed a high payload dual-arm robot, in which the forearm module is replaceable to meet the assigned task, such as object handling or lifting humans in a rescue operation. With each forearm module specialized for an assigned task (e.g. safety for rescue and redundant joints for object handling task), the robot can conduct various tasks more effectively than could be done previously. In this paper, the design of the high payload dual-arm robot with replaceable forearm function is described in detail. Two forearms are developed here. Each of forearm has quite a different goal. One of the forearms is specialized for human rescue in human familiar flat aspect and compliance parts. Other is for general heavy objects, more than 30 kg, handling with high degree of freedom more than 7.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권9호
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• pp.407-418
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• 2023

MultiOn(Multi-Object Goal Visual Navigation)은 에이전트가 미지의 실내 환경 내 임의의 위치에 놓인 다수의 목표 물체들을 미리 정해준 일정한 순서에 따라 찾아가야 하는 매우 어려운 시각적 탐색 이동 작업이다. MultiOn 작업을 위한 기존의 모델들은 행동 선택을 위해 시각적 외관 지도나 목표 지도와 같은 단일 맥락 지도만을 이용할 뿐, 다양한 멀티모달 맥락정보에 관한 종합적인 관점을 활용할 수 없다는 한계성을 가지고 있다. 이와 같은 한계성을 극복하기 위해, 본 논문에서는 MultiOn 작업을 위한 새로운 심층 신경망 기반의 에이전트 모델인 MCFMO(Multimodal Context Fusion for MultiOn tasks)를 제안한다. 제안 모델에서는 입력 영상의 시각적 외관 특징외에 환경 물체의 의미적 특징, 목표 물체 특징도 함께 포함한 멀티모달 맥락 지도를 행동 선택에 이용한다. 또한, 제안 모델은 점-단위 합성곱 신경망 모듈을 이용하여 3가지 서로 이질적인 맥락 특징들을 효과적으로 융합한다. 이 밖에도 제안 모델은 효율적인 이동 정책 학습을 유도하기 위해, 목표 물체의 관측 여부와 방향, 그리고 거리를 예측하는 보조 작업 학습 모듈을 추가로 채용한다. 본 논문에서는 Habitat-Matterport3D 시뮬레이션 환경과 장면 데이터 집합을 이용한 다양한 정량 및 정성 실험들을 통해, 제안 모델의 우수성을 확인하였다.

• Journal of Information Processing Systems
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• 제17권1호
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• pp.124-135
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• 2021

Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.300-309
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• 2018

Detection of vanishing point is a challenging task in the situations where there are several structures with straight lines. Commonly used approaches for determining vanishing points involves finding the straight lines using edge detection and Hough transform methods. This approach often fails to perform effectively when there are a lot of straight lines found. The lines not meeting at a vanishing point are considered to be noises. In such situation, finding right candidate lines for detecting vanishing points is not a simple task. This paper proposes to use reference objects for vanishing point detection. By analyzing a reference object, it identifies the contour of the object, and derives a polygon from the contour information. Then the edges of the detected polygon are used to find the vanishing points. Our experimental results show that the proposed approach can detect vanishing points with comparable accuracy to the existing edge detection based method. Our approach can also be applied effectively even to complex situations, where too many lines generated by the existing methods make it difficult to select right lines for the vanishing points.

• 한국정밀공학회지
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• 제20권1호
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• pp.99-106
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the there dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The insertion task of an electric line into a sleeve is selected as the typical task of the maintenance of active electric power distribution lines in this paper. A modified hough transform is applied to the recognition of the center of electric line and optimal target position calculation method is newly derived in order to recognize the center 3 dimensional position of the electric line. By the proposed method, it is proved that the center position of the electric line can be recognized without respect to the noise of image and the shape of electric lines and the insertion task of an electric tine is realized.