找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computer Vision, Imaging and Computer Graphics Theory and Applications; 15th International J Kadi Bouatouch,A. Augusto de Sousa,Jose Braz C

[復(fù)制鏈接]
樓主: 不同
31#
發(fā)表于 2025-3-26 23:42:03 | 只看該作者
CSG Tree Extraction from 3D Point Clouds and Meshes Using a Hybrid Approachrithm (GA) for convex polytope generation. It directly transforms 3D point clouds or triangle meshes into solid primitives. The filtered primitive set is then used as input for a GA-based CSG extraction stage. We evaluate two different CSG extraction methodologies and furthermore compare our pipeline to current state-of-the-art methods.
32#
發(fā)表于 2025-3-27 03:45:10 | 只看該作者
Intention Understanding for Human-Aware Mobile Robots: Comparing Cues and the Effect of Demographicshree lighting schemes and tested them out in an online experiment. We found that signals resembling automotive signaling work the best also for logistic mobile robots. We further find that people’s opinion of these signaling methods will be influenced by their demographic background (gender, age).
33#
發(fā)表于 2025-3-27 06:00:10 | 只看該作者
34#
發(fā)表于 2025-3-27 13:02:40 | 只看該作者
35#
發(fā)表于 2025-3-27 16:14:43 | 只看該作者
36#
發(fā)表于 2025-3-27 21:05:36 | 只看該作者
Intention Understanding for Human-Aware Mobile Robots: Comparing Cues and the Effect of Demographicsret what the robot’s intentions are. This is especially important when a robot is driving down a crowded corridor. It is essential for people in its vicinity to understand which way the robot wants to go next. To explore what signals are the best for conveying its intention to turn, we implemented t
37#
發(fā)表于 2025-3-28 00:58:09 | 只看該作者
38#
發(fā)表于 2025-3-28 04:41:12 | 只看該作者
Scalable Visual Exploration of?3D Shape Databases via?Feature Synthesis and?Selectionensionality reduction of feature vectors extracted from shape descriptions. We address the problem of feature extraction by exploring both combinations of hand-engineered geometric features and using the latent feature vectors generated by a deep learning classification method, and discuss the compa
39#
發(fā)表于 2025-3-28 09:25:22 | 只看該作者
40#
發(fā)表于 2025-3-28 14:30:56 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-19 19:33
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
彩票| 萨迦县| 罗定市| 商丘市| 瓦房店市| 乐至县| 韩城市| 汶上县| 松桃| 塔城市| 万山特区| 贺兰县| 新营市| 广德县| 奉化市| 务川| 磐安县| 宾川县| 宿迁市| 安龙县| 巴马| 慈溪市| 洪湖市| 碌曲县| 凤台县| 云南省| 宜昌市| 米易县| 昌平区| 灌南县| 桂平市| 酒泉市| 若尔盖县| 灯塔市| 中牟县| 涟水县| 宿迁市| 阳泉市| 灌南县| 香港 | 德惠市|