Saved in:
| Other Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania
IGI Global
2022
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| Subjects: | |
| Links: | https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 https://doi.org/10.4018/978-1-7998-9434-6 |
| Summary: | Challenges and applications for hand gesture recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students |
| Item Description: | Includes bibliographical references and index Chapter 1. Skin-colour-based hand segmentation techniques -- Chapter 2. Hand gesture recognition through depth sensors -- Chapter 3. Hand gesture recognition: the road ahead -- Chapter 4. IoT-based wearable sensors: hand gesture recognition -- Chapter 5. Recent advancements in design and implementation of automated sign language recognition systems -- Chapter 6. Hidden Markov model for gesture recognition -- Chapter 7. A six-stream CNN fusion-based human activity recognition on RGBD data: a novel framework -- Chapter 8. Multi-input CNN-LSTM for end-to-end Indian sign language recognition: a use case with wearable sensors -- Chapter 9. Lightweight convnet model for american sign language hand gesture recognition -- Chapter 10. Applications of hand gesture recognition -- Chapter 11. Application of HGR rock-paper-scissors model. - Mode of access: World Wide Web |
| Physical Description: | 1 Online-Ressource (249 Seiten) |
| ISBN: | 9781799894360 |
| DOI: | 10.4018/978-1-7998-9434-6 |
Staff View
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| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:39:20Z |
| institution | BVB |
| isbn | 9781799894360 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033620744 |
| oclc_num | 1322807688 |
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| physical | 1 Online-Ressource (249 Seiten) |
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| publishDate | 2022 |
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| publisher | IGI Global |
| record_format | marc |
| spellingShingle | Challenges and applications for hand gesture recognition Computer vision |
| title | Challenges and applications for hand gesture recognition |
| title_auth | Challenges and applications for hand gesture recognition |
| title_exact_search | Challenges and applications for hand gesture recognition |
| title_full | Challenges and applications for hand gesture recognition edited by Lalit Kane, Bhupesh Kumar Dewangan and Tanupriya Choudhury |
| title_fullStr | Challenges and applications for hand gesture recognition edited by Lalit Kane, Bhupesh Kumar Dewangan and Tanupriya Choudhury |
| title_full_unstemmed | Challenges and applications for hand gesture recognition edited by Lalit Kane, Bhupesh Kumar Dewangan and Tanupriya Choudhury |
| title_short | Challenges and applications for hand gesture recognition |
| title_sort | challenges and applications for hand gesture recognition |
| topic | Computer vision |
| topic_facet | Computer vision |
| url | https://doi.org/10.4018/978-1-7998-9434-6 |
| work_keys_str_mv | AT choudhurytanupriya challengesandapplicationsforhandgesturerecognition AT dewanganbhupesh challengesandapplicationsforhandgesturerecognition AT kanelalit challengesandapplicationsforhandgesturerecognition |