Soni et al., 2019 - Google Patents
Automated fall detection from a camera using support vector machineSoni et al., 2019
- Document ID
- 1182348465118645609
- Author
- Soni P
- Choudhary A
- Publication year
- Publication venue
- 2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP)
External Links
Snippet
Falls and fall-related fractures of a person is a major health problem and this issue is increasing day-by-day, especially for elderly who live alone. In this paper, we propose a camera based, novel, real-time automated fall detection framework for indoor environments …
- 238000001514 detection method 0 title abstract description 46
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
- G06K9/00369—Recognition of whole body, e.g. static pedestrian or occupant recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
- G06T2207/30201—Face
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00288—Classification, e.g. identification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00228—Detection; Localisation; Normalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lotfi et al. | Supporting independent living for older adults; employing a visual based fall detection through analysing the motion and shape of the human body | |
Vishnu et al. | Human fall detection in surveillance videos using fall motion vector modeling | |
Wang et al. | Fall detection based on dual-channel feature integration | |
Kong et al. | Learning spatiotemporal representations for human fall detection in surveillance video | |
Zhao et al. | Real-time detection of fall from bed using a single depth camera | |
Soni et al. | Automated fall detection from a camera using support vector machine | |
Kepski et al. | Fall detection using ceiling-mounted 3d depth camera | |
Alaoui et al. | Fall detection for elderly people using the variation of key points of human skeleton | |
Yun et al. | Human fall detection in videos by fusing statistical features of shape and motion dynamics on Riemannian manifolds | |
Jansi et al. | Detection of fall for the elderly in an indoor environment using a tri-axial accelerometer and Kinect depth data | |
Poonsri et al. | Fall detection using Gaussian mixture model and principle component analysis | |
Lezzar et al. | Camera-based fall detection system for the elderly with occlusion recognition | |
Yun et al. | Human fall detection via shape analysis on Riemannian manifolds with applications to elderly care | |
Albawendi et al. | Video based fall detection using features of motion, shape and histogram | |
Serpa et al. | Evaluating pose estimation as a solution to the fall detection problem | |
Soni et al. | Grassmann manifold based framework for automated fall detection from a camera | |
Qian et al. | Home environment fall detection system based on a cascaded multi-SVM classifier | |
Merrouche et al. | Fall detection using head tracking and centroid movement based on a depth camera | |
Hung et al. | Fall detection with two cameras based on occupied area | |
Khraief et al. | Convolutional neural network based on dynamic motion and shape variations for elderly fall detection | |
Thuc et al. | An effective video-based model for fall monitoring of the elderly | |
Khraief et al. | Vision-based fall detection for elderly people using body parts movement and shape analysis | |
Ezatzadeh et al. | ViFa: an analytical framework for vision-based fall detection in a surveillance environment | |
Biswas et al. | A literature review of current vision based fall detection methods | |
ElSayed et al. | Ambient and wearable sensing for gait classification in pervasive healthcare environments |