2022 International Workshop on Intelligent Systems (IWIS)最新文献

TASuRe: Text Aware Super-Resolution TASuRe:文本感知超分辨率

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920903

Elena Filonenko, A. Filonenko, K. Jo

引用次数: 0

Attribute estimation using pedestrian clothing and autonomous mobile robot navigation based on it 基于行人服装的属性估计及其自主移动机器人导航

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920723

Hidenao Takahashi, Nami Takino, H. Hashimoto, D. Chugo, S. Muramatsu, S. Yokota, Jin-Hua She, H. Hashimoto

{"title":"Attribute estimation using pedestrian clothing and autonomous mobile robot navigation based on it","authors":"Hidenao Takahashi, Nami Takino, H. Hashimoto, D. Chugo, S. Muramatsu, S. Yokota, Jin-Hua She, H. Hashimoto","doi":"10.1109/IWIS56333.2022.9920723","DOIUrl":"https://doi.org/10.1109/IWIS56333.2022.9920723","url":null,"abstract":"This paper proposes a new method for estimating the attributes of a pedestrian, e.g. an office worker or a student, from the pedestrian's clothing and, based on the estimation results, a method for efficiently navigating an autonomous mobile robot while safely avoiding pedestrians. The robot can estimate the organization the pedestrians belong to by learning in advance the clothing of pedestrians that frequently appear in the city in which the is travelling, e.g. the uniforms of certain high school students. Furthermore, the robot is given the direction in which the person in that organization is likely to be heading at the current time, so it uses this information to estimate the future walking trajectory of that pedestrian and design a running path that is less likely to prevent that pedestrian from walking. We use the artificial potential method to design the robot's running trajectory. Even if pedestrians with different attributes are detected in the robot's running path, our proposed robot can efficiently reach its destination while avoiding those pedestrians appropriately in real time. The effectiveness of the proposed method was confirmed by computer simulations and subjects' experiments with our prototype robot.","PeriodicalId":340399,"journal":{"name":"2022 International Workshop on Intelligent Systems (IWIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123064458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensor Fusion of Camera and 2D LiDAR for Self-Driving Automobile in Obstacle Avoidance Scenarios 自动驾驶汽车避障场景中摄像头与2D激光雷达传感器融合

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920917

Tan-Thien-Nien Nguyen, Thanh-Danh Phan, Minh-Thien Duong, Chi-Tam Nguyen, Hong-Phong Ly, M. Le

{"title":"Sensor Fusion of Camera and 2D LiDAR for Self-Driving Automobile in Obstacle Avoidance Scenarios","authors":"Tan-Thien-Nien Nguyen, Thanh-Danh Phan, Minh-Thien Duong, Chi-Tam Nguyen, Hong-Phong Ly, M. Le","doi":"10.1109/IWIS56333.2022.9920917","DOIUrl":"https://doi.org/10.1109/IWIS56333.2022.9920917","url":null,"abstract":"Obstacle dodging and overtaking are the pivotal tasks ensuring safety for self-driving automobiles. Multi-sensors fusion is the must-required condition to explore the entire surrounding information. This paper proposes a novel frontal dynamic car dodging strategy for automobiles with the left-hand side steering wheel by fusion of a camera and 2D LiDAR features. To begin with, we improve the LiteSeg model to extract the segmented mask, which can determine the drivable area and the avoiding direction. In addition to a camera, 2D LiDAR is used to check the scene information on the right side, which the camera's range cannot cover. As for point clouds output of 2D LiDAR, we adopt the Adaptive Breakpoint Detection (defined as ABD) algorithm to cluster the objects in a scanning plane. Subsequently, the RANSAC algorithm forms a straight line from the clustered point clouds to determine the boundary of the right-side obstacle. Besides, we compute the distance from LiDAR to the estimated straight line to maintain a safe distance when overtaking. Last but not least, the post-processing results of the two devices are fused to decide on the obstacle dodging and overtaking. The comprehensive experiments reveal that our self-driving automobile could perform well on the university campus in diverse scenarios.","PeriodicalId":340399,"journal":{"name":"2022 International Workshop on Intelligent Systems (IWIS)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116420187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Fast Real-time Face Gender Detector on CPU using Superficial Network with Attention Modules 基于关注模块的CPU表面网络快速实时人脸性别检测

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920714

Adri Priadana, M. D. Putro, Changhyun Jeong, K. Jo

{"title":"A Fast Real-time Face Gender Detector on CPU using Superficial Network with Attention Modules","authors":"Adri Priadana, M. D. Putro, Changhyun Jeong, K. Jo","doi":"10.1109/IWIS56333.2022.9920714","DOIUrl":"https://doi.org/10.1109/IWIS56333.2022.9920714","url":null,"abstract":"A gender detector has become an essential part of digital signage to support the decision to provide relevant ads for each audience. Application installed in digital signage must be capable of running on low-cost or CPU devices to minimize system costs. This study proposed a fast face gender detector (Gender-CPU) that can sprint in real-time on CPU devices implemented on digital signage. The proposed architecture contains a superficial network with attention modules (SufiaNet). This architecture only consists of three convolution layers, making it super shallow and generating a small number of parameters. In order to redeem the lack of a super shallow network, the global attention module is assigned to improve the quality of the feature map resulting from the previous convolution layers. In the experiment, the training and validation process is conducted on the UTKFace, the Adience Benchmark, and the Labeled Faces in the Wild (LFW) datasets. The SufiaNet gains competitive accuracy compared to other common and light architectures on the three datasets. Moreover, the detector can run 84.97 frames per second on a CPU device, which is fast to run in real-time.","PeriodicalId":340399,"journal":{"name":"2022 International Workshop on Intelligent Systems (IWIS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128504360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Safe Cooperative Intersection of Autonomous and Connected Robots: Trajectory and Schedule Optimization 自主与互联机器人的安全协同交叉口:轨迹与调度优化

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920759

Wendan Du, A. Abbas-Turki, A. Koukam, K. Jo

引用次数: 1

Lightweight Bird Eye View Detection Network with Bridge Block Based on YOLOv5 基于YOLOv5的轻型桥块鸟瞰图检测网络

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920755

Jehwan Choi, Kanghyun Jo

引用次数: 0

Automatic Feature Detection and Classification for Watermelon (Citrillus lanatus) 西瓜特征自动检测与分类

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920868

J. Sánchez-Galán, Anel Henry Royo, K. Jo, Danilo Cáceres Hernández

引用次数: 1

A Study on Efficient Multi-task Networks for Multiple Object Tracking 多目标跟踪的高效多任务网络研究

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920879

Xuan-Thuy Vo, T. Tran, Duy-Linh Nguyen, K. Jo

{"title":"A Study on Efficient Multi-task Networks for Multiple Object Tracking","authors":"Xuan-Thuy Vo, T. Tran, Duy-Linh Nguyen, K. Jo","doi":"10.1109/IWIS56333.2022.9920879","DOIUrl":"https://doi.org/10.1109/IWIS56333.2022.9920879","url":null,"abstract":"Multiple object tracking involves multi-task learning to handle object detection and data association tasks concurrently. Conventionally, object detection consists of object classification and object localization (e.g., object regression) tasks, and data association is treated as a classification task. However, various tasks can cause inconsistent learning due to that the learning targets of object detection and data association tasks are different. Object detection focuses on positional information of objects while data association requires strong semantic information to identify same object target. Besides, advantageous character of multi-task learning is the correlation between tasks, and adopting such character in learning the networks can result in better generalization performance. However, existing multiple object tracking methods learn this information by treating multi-task branches independently. To understand the behaviours of multi-task networks in multiple object tracking, in this paper, we explore task-dependent representations through empirical experiments and observe that multi-task branches in multiple object tracking are complementary. To better learn such information, we introduce a novel Correlation Estimation (CE) module to estimate the correlation between object classification and bounding box regression based on statistical features of box regression quality. Finally, extensive experiments are conducted on the benchmark dataset MOT17. As a result, our method outperforms state-of-the-art online trackers without requiring additional training datasets.","PeriodicalId":340399,"journal":{"name":"2022 International Workshop on Intelligent Systems (IWIS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116060485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Disparity Map for Moving Object Position Estimation in Pan Tilt Camera Images 利用视差图估计平移倾斜相机图像中的运动目标位置

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920838

Tomasz Kocejko, J. Rumiński, K. Jo

引用次数: 0

Graph-based Attribute-aware Unsupervised Person Re-identification with Contrastive learning 基于图的属性感知无监督人再识别与对比学习

2022 International Workshop on Intelligent Systems (IWIS) Pub Date : 2022-08-17 DOI: 10.1109/IWIS56333.2022.9920894

Ge Cao, Qing Tang, Kanghyun Jo

引用次数: 2