![Gesture recognition [electronic resource]](https://image.aladin.co.kr/product/10588/85/cover/331957020x_2.jpg)
| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045993548 | |
| 005 | 20190814104233 | |
| 006 | m d | |
| 007 | cr | |
| 008 | 190806s2017 sz a ob 000 0 eng d | |
| 020 | ▼a 9783319570204 | |
| 020 | ▼a 9783319570211 (e-book) | |
| 040 | ▼a 211009 ▼c 211009 ▼d 211009 | |
| 050 | 4 | ▼a Q334-342 |
| 082 | 0 4 | ▼a 006.42 ▼2 23 |
| 084 | ▼a 006.42 ▼2 DDCK | |
| 090 | ▼a 006.42 | |
| 245 | 0 0 | ▼a Gesture recognition ▼h [electronic resource] / ▼c Sergio Escalera, Isabelle Guyon, Vassilis Athitsos, editors. |
| 260 | ▼a Cham : ▼b Springer, ▼c c2017. | |
| 300 | ▼a 1 online resource (xii, 578 p.) : ▼b ill. | |
| 490 | 1 | ▼a The Springer Series on Challenges in Machine Learning, ▼x 2520-131X, ▼x 2520-1328 (electronic) |
| 500 | ▼a Title from e-Book title page. | |
| 504 | ▼a Includes bibliographical references. | |
| 505 | 0 | ▼a Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5. |
| 520 | ▼a This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images 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 sources, feature extraction, learning, and recognition of gestures. | |
| 530 | ▼a Issued also as a book. | |
| 538 | ▼a Mode of access: World Wide Web. | |
| 650 | 0 | ▼a Optical pattern recognition. |
| 650 | 0 | ▼a Gesture ▼x Data processing. |
| 650 | 0 | ▼a Machine learning. |
| 700 | 1 | ▼a Escalera, Sergio. |
| 700 | 1 | ▼a Guyon, Isabelle. |
| 700 | 1 | ▼a Athitsos, Vassilis. |
| 830 | 0 | ▼a The Springer Series on Challenges in Machine Learning. |
| 856 | 4 0 | ▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-3-319-57021-1 |
| 945 | ▼a KLPA | |
| 991 | ▼a E-Book(소장) |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/e-Book 컬렉션/ | 청구기호 CR 006.42 | 등록번호 E14016754 | 도서상태 대출불가(열람가능) | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
This book presents a selection of chapters, written by leading international researchers, related to the automatic analysis of gestures from still images 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 sources, feature extraction, learning, and recognition of gestures.
정보제공 :
목차
Preface.- Chapter 1.- Chapter 2.- Chapter 3.- Chapter 4.- Chapter 5.
정보제공 :