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: Gesture Recognition; Sergio Escalera,Isabelle Guyon,Vassilis Athitsos Book 2017 Springer International Publishing AG 2017 Artificial intel

[復制鏈接]
樓主: 搖尾乞憐
51#
發(fā)表于 2025-3-30 10:38:43 | 只看該作者
One-Shot-Learning Gesture Recognition Using HOG-HOF Features,together with variants of a Dynamic Time Warping technique. Both methods outperform other published methods and help narrow the gap between human performance and algorithms on this task. The code is publicly available in the MLOSS repository.
52#
發(fā)表于 2025-3-30 13:29:18 | 只看該作者
Transfer Learning Decision Forests for Gesture Recognition,e manifold structure of the feature space. We show that both of them are important to achieve higher accuracy. Our experiments demonstrate improvements over traditional decision forests in the ChaLearn Gesture Challenge and MNIST data set. They also compare favorably against other state-of-the-art classifiers.
53#
發(fā)表于 2025-3-30 18:36:35 | 只看該作者
Book 2017ages and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different source
54#
發(fā)表于 2025-3-30 23:50:50 | 只看該作者
2520-131X e reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures..978-3-319-86059-6978-3-319-57021-1Series ISSN 2520-131X Series E-ISSN 2520-1328
55#
發(fā)表于 2025-3-31 01:54:55 | 只看該作者
Richard F. Link,George S. Koch Jr.ferring the optimal labeling of this hierarchical model. The pose information captured by this hierarchical model can also be used as a intermediate representation for other high-level tasks. We demonstrate it in action recognition from static images.
56#
發(fā)表于 2025-3-31 07:36:10 | 只看該作者
57#
發(fā)表于 2025-3-31 12:04:34 | 只看該作者
Discriminative Hierarchical Part-Based Models for Human Parsing and Action Recognition,ferring the optimal labeling of this hierarchical model. The pose information captured by this hierarchical model can also be used as a intermediate representation for other high-level tasks. We demonstrate it in action recognition from static images.
58#
發(fā)表于 2025-3-31 13:33:46 | 只看該作者
59#
發(fā)表于 2025-3-31 20:43:54 | 只看該作者
60#
發(fā)表于 2025-3-31 22:14:46 | 只看該作者
Book 2017 that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures..
 關于派博傳思  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 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 15:01
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
吴川市| 永泰县| 桃源县| 滨海县| 保定市| 仙游县| 龙海市| 东至县| 新巴尔虎左旗| 阿克陶县| 平陆县| 达州市| 岳池县| 丹阳市| 宁强县| 商水县| 鄂托克前旗| 夏津县| 佛坪县| 福贡县| 永新县| 怀柔区| 晋中市| 高密市| 黑河市| 谷城县| 凤庆县| 兰西县| 莒南县| 青河县| 抚松县| 襄城县| 白朗县| 门头沟区| 高密市| 莲花县| 全州县| 新乐市| 肃宁县| 荆州市| 东乌|