Cargando…
Human Activity Analysis in Visual Surveillance and Healthcare
Long description: An automatic recognition of human activities enables their use in several interesting applications of daily life. This dissertation emphases on the analysis of human activities in a visual surveillance scenario and the classification of physical activities in the therapeutic proced...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin :
Logos Verlag Berlin,
2018.
|
| Colección: | Studien Zur Mustererkennung Ser.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mu 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_on1085170343 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr |n|---||||| | ||
| 008 | 190209s2018 gw o 000 0 eng d | ||
| 040 | |a EBLCP |b eng |e pn |c EBLCP |d YDX |d OCLCQ |d REDDC |d OCLCO |d SFB |d OCLCL | ||
| 019 | |a 1085202045 |a 1415905044 | ||
| 020 | |a 9783832590284 | ||
| 020 | |a 3832590285 | ||
| 020 | |z 3832548076 | ||
| 020 | |z 9783832548070 | ||
| 029 | 1 | |a AU@ |b 000075612436 | |
| 035 | |a (OCoLC)1085170343 |z (OCoLC)1085202045 |z (OCoLC)1415905044 | ||
| 050 | 4 | |a RA410.5 |b .K436 2018 | |
| 082 | 0 | 4 | |a 362.1 |q OCoLC |2 23/eng/20230216 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Khan, Muhammad Hassan. | |
| 245 | 1 | 0 | |a Human Activity Analysis in Visual Surveillance and Healthcare |
| 260 | |a Berlin : |b Logos Verlag Berlin, |c 2018. | ||
| 300 | |a 1 online resource (162 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Studien Zur Mustererkennung Ser. ; |v v. 45 | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Intro; 1 Introduction; 1.1 Problem; 1.2 Contribution; 1.3 Overview; 2 RelatedWork; 2.1 Terminology; 2.2 Gait Representation; 2.2.1 Model-based Approaches; 2.2.2 Appearance-based Approaches; 2.3 Cross-view Gait Recognition; 2.3.1 View-invariant Gait Descriptor; 2.3.2 3D View Gait Descriptor; 2.3.3 View Transformation Model; 2.4 Benchmark Gait Databases; 2.5 Movement Analysis; 2.5.1 Visual Sensor-based Approaches; 2.5.2 Motion Sensor-based Algorithms; 3 Single-view Gait Recognition; 3.1 Gait Recognition using Spatiotemporal Motion Characteristics; 3.1.1 Motion Descriptors | |
| 505 | 8 | |a 3.1.2 Codebook Generation3.1.3 Feature Encoding; 3.1.4 Dimensionality Reduction; 3.1.5 Classification; 3.1.6 Experiments and Results; 3.2 Adaptation of Generic Codebook for Gait Recognition Algorithms; 3.2.1 Experiments and Results; 3.2.2 Discussion; 3.3 Summary; 4 Cross-view Gait Recognition; 4.1 Gait Representation; 4.2 View Transfer Model; 4.3 Cross-view Gait Representation and Classification; 4.4 Experiments and Results; 4.5 Summary; 5 Movement Analysis of Human Body Parts; 5.1 A Deformable Part-based Model for Movement Analysis of Infants; 5.2 Template-based Model for Infant's Detection | |
| 505 | 8 | |a 5.3 Infant's Motion Analysis5.4 Model Training; 5.5 Experiments and Results; 5.6 Summary; 6 Evaluation of the Therapeutic Procedure; 6.1 A Vision-based Framework to Evaluate the Physiotherapy; 6.1.1 Data Pre-processing; 6.1.2 Patient Body Detection; 6.1.3 Pose Representation; 6.1.4 Classification; 6.1.5 Experiments and Results; 6.2 A Deformable Part-based Model to Evaluate the Physiotherapy; 6.3 Summary; 7 Conclusion and FutureWork; 7.1 Conclusion; 7.2 FutureWork; Abbreviations; Mathematical Symbols; List of Figures; List of Tables; Bibliography; Own Publications; Curriculum Vitae | |
| 520 | |a Long description: An automatic recognition of human activities enables their use in several interesting applications of daily life. This dissertation emphases on the analysis of human activities in a visual surveillance scenario and the classification of physical activities in the therapeutic procedure using visual data. The first part of the dissertation proposes a robust gait representation to recognise the identity of a person using his/her walking style, dealing with its several real world challenges as well as taking into consideration the effects of cross-view recognition. In the second part, a complete framework is proposed to capture and analyse the movement of different body parts in human which is useful in the clinical assessment to detect any movement disorders and the assessment of the desired therapeutic program. | ||
| 546 | |a English with German abstract, pages ix-x. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Medical care. | |
| 650 | 0 | |a Social medicine. | |
| 650 | 2 | |a Patient Care | |
| 650 | 6 | |a Soins médicaux. | |
| 758 | |i has work: |a Human activity analysis in visual surveillance and healthcare (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFxx3tyV96kGT3KpTGKprm |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Khan, Muhammad Hassan. |t Human Activity Analysis in Visual Surveillance and Healthcare. |d Berlin : Logos Verlag Berlin, ©2018 |z 9783832548070 |
| 830 | 0 | |a Studien Zur Mustererkennung Ser. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5662538 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5662538 | ||
| 938 | |a YBP Library Services |b YANK |n 16032398 | ||
| 994 | |a 92 |b IZTAP | ||