Li et al., 2014 - Google Patents
QueueSense: Collaborative recognition of queuing on mobile phonesLi et al., 2014
View PDF- Document ID
- 991133499366329221
- Author
- Li Q
- Han Q
- Cheng X
- Sun L
- Publication year
- Publication venue
- 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
External Links
Snippet
Nowadays people spend a substantial amount of time waiting in different places such as supermarkets and amusement parks. Detecting the status of queuing may benefit both users and business. In this paper, we present QueueSense, a queuing recognition system on …
- 238000001514 detection method 0 abstract description 8
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W4/00—Mobile application services or facilities specially adapted for wireless communication networks
- H04W4/02—Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
- H04W4/023—Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W4/00—Mobile application services or facilities specially adapted for wireless communication networks
- H04W4/02—Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
- H04W4/025—Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using location based information parameters
-
- 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
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- 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
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Miluzzo et al. | Darwin phones: the evolution of sensing and inference on mobile phones | |
Hossain | Cloud-supported cyber–physical localization framework for patients monitoring | |
Sen et al. | Grumon: Fast and accurate group monitoring for heterogeneous urban spaces | |
Li et al. | QueueSense: Collaborative recognition of queuing on mobile phones | |
Coskun et al. | Phone position/placement detection using accelerometer: Impact on activity recognition | |
Roy et al. | Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments | |
Hoseini-Tabatabaei et al. | A survey on smartphone-based systems for opportunistic user context recognition | |
Kjærgaard et al. | Detecting pedestrian flocks by fusion of multi-modal sensors in mobile phones | |
Nickel et al. | Authentication of smartphone users based on the way they walk using k-NN algorithm | |
Mahbub et al. | PATH: person authentication using trace histories | |
Vhaduri et al. | Discovering places of interest using sensor data from smartphones and wearables | |
Lee et al. | Non-obstructive room-level locating system in home environments using activity fingerprints from smartwatch | |
Lau et al. | Extracting point of interest and classifying environment for low sampling crowd sensing smartphone sensor data | |
Korany et al. | Counting a stationary crowd using off-the-shelf wifi | |
Du et al. | Group mobility classification and structure recognition using mobile devices | |
Honnef et al. | Zero-effort indoor continuous social distancing monitoring system | |
Khan et al. | Infrastructure-less occupancy detection and semantic localization in smart environments | |
Shao et al. | BLEDoorGuard: A device-free person identification framework using bluetooth signals for door access | |
Li et al. | Collaborative recognition of queuing behavior on mobile phones | |
Wang et al. | A survey of user authentication based on channel state information | |
He et al. | Crowd-flow graph construction and identification with spatio-temporal signal feature fusion | |
Liang et al. | CircleSense: a pervasive computing system for recognizing social activities | |
Khan et al. | Sensepresence: Infrastructure-less occupancy detection for opportunistic sensing applications | |
Maekawa et al. | How well can a user’s location privacy preferences be determined without using GPS location data? | |
Rizk et al. | Vaccinated, what next? an efficient contact and social distance tracing based on heterogeneous telco data |