BibSLEIGH
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Used together with:
detect (17)
base (9)
navig (7)
use (6)
featur (6)

Stem pedestrian$ (all stems)

52 papers:

CHICHI-2015-PfeifferDSAR #using
Cruise Control for Pedestrians: Controlling Walking Direction using Electrical Muscle Stimulation (MP, TD, SS, FA, MR), pp. 2505–2514.
HCIDHM-EH-2015-TianLYJCS #analysis #scalability #video
Single-Variable Scenario Analysis of Vehicle-Pedestrian Potential Crash Based on Video Analysis Results of Large-Scale Naturalistic Driving Data (RT, LL, KY, FJ, YC, RS), pp. 295–304.
CASECASE-2014-LiWC #using
Pedestrian tracking system by using human shape prior model (KCL, HCW, JMC), pp. 1139–1143.
ICPRICPR-2014-AhmetovicBGM #locality #named #performance #precise
ZebraRecognizer: Efficient and Precise Localization of Pedestrian Crossings (DA, CB, AG, SM), pp. 2566–2571.
ICPRICPR-2014-BartoliLKBB #adaptation #detection #multi #performance
Unsupervised Scene Adaptation for Faster Multi-scale Pedestrian Detection (FB, GL, SK, ADB, ADB), pp. 3534–3539.
ICPRICPR-2014-BrownFP #detection #self #using
Temporal Non-maximum Suppression for Pedestrian Detection Using Self-Calibration (LMGB, RSF, SP), pp. 2239–2244.
ICPRICPR-2014-GoldhammerDBGS #network
Pedestrian’s Trajectory Forecast in Public Traffic with Artificial Neural Networks (MG, KD, UB, AG, BS), pp. 4110–4115.
ICPRICPR-2014-HtikeH #adaptation #detection #performance #video
Efficient Non-iterative Domain Adaptation of Pedestrian Detectors to Video Scenes (KKH, DCH), pp. 654–659.
ICPRICPR-2014-MadrigalHL #multi
Intention-Aware Multiple Pedestrian Tracking (FM, JBH, FL), pp. 4122–4127.
ICPRICPR-2014-MeloLMS #approach #detection
An Optimized Sliding Window Approach to Pedestrian Detection (VHCdM, SL, DM, WRS), pp. 4346–4351.
ICPRICPR-2014-NilssonAGF #detection #using
Pedestrian Detection Using Augmented Training Data (JN, PA, IYHG, JF), pp. 4548–4553.
ICPRICPR-2014-PedagadiOB #detection
Integral Line Scan Features for Pedestrian Detection (SP, JO, BAB), pp. 2383–2388.
ICPRICPR-2014-SmedtBTG #combinator #detection #multi
The Combinator: Optimal Combination of Multiple Pedestrian Detectors (FDS, KVB, TT, TG), pp. 3522–3527.
ICPRICPR-2014-YamadaM #approach #behaviour #using
Estimating Driver Awareness of Crossing Pedestrians While Turning Left Based on Vehicle Behavior Using Bayesian Approach (KY, TM), pp. 1898–1903.
ICPRICPR-2014-ZhangKBC #detection
Center-Surround Contrast Features for Pedestrian Detection (SZ, DAK, CB, ABC), pp. 2293–2298.
CASECASE-2013-GaoLZC #social
A modified social force model considering relative velocity of pedestrians (YG, PBL, HZ, TC), pp. 747–751.
HCIHCI-UC-2013-FurukawaN #navigation
A Pedestrian Navigation Method for User’s Safe and Easy Wayfinding (HF, YN), pp. 156–165.
HCIHIMI-HSM-2013-ItoK
Autonomous Locomotion Based on Interpersonal Contexts of Pedestrian Areas for Intelligent Powered Wheelchair (TI, MK), pp. 480–489.
SEKESEKE-2013-AgrawalT #locality #smarttech
Smart Phone Based Indoor Pedestrian Localization System (S) (LA, DT), pp. 283–286.
CHICHI-2012-GuyT #named #navigation #visual notation
CrossingGuard: exploring information content in navigation aids for visually impaired pedestrians (RTG, KNT), pp. 405–414.
ICPRICPR-2012-HsuNWC #component #using
Pedestrian tracking in low contrast regions using aggregated background model and Silhouette Components (GSH, HPN, CHW, SLC), pp. 3680–3683.
ICPRICPR-2012-LePB #detection #navigation #people
Pedestrian lane detection for assistive navigation of blind people (MCL, SLP, AB), pp. 2594–2597.
ICPRICPR-2012-LiangYCJ #evaluation #representation
Evaluation of local feature descriptors and their combination for pedestrian representation (JL, QY, JC, JJ), pp. 2496–2499.
ICPRICPR-2012-LinL #bottom-up #process #top-down
Integrating bottom-up and top-down processes for accurate pedestrian counting (YL, NL), pp. 2508–2511.
ICPRICPR-2012-NodariVG #artificial reality #image #privacy
Digital privacy: Replacing pedestrians from Google Street View images (AN, MV, IG), pp. 2889–2893.
ICPRICPR-2012-San-BiagioUCCCM #approach #classification #kernel #learning #multi
A multiple kernel learning approach to multi-modal pedestrian classification (MSB, AU, MC, MC, UC, VM), pp. 2412–2415.
ICPRICPR-2012-ShaukatGWB #approach #bottom-up #detection #top-down
Meeting in the Middle: A top-down and bottom-up approach to detect pedestrians (AS, AG, DW, RB), pp. 874–877.
ICPRICPR-2012-VazquezLP #adaptation #detection
Unsupervised domain adaptation of virtual and real worlds for pedestrian detection (DV, AML, DP), pp. 3492–3495.
ICPRICPR-2012-WakayamaDDIMT #detection #estimation #performance #visual notation
Estimation of the human performance for pedestrian detectability based on visual search and motion features (MW, DD, KD, II, HM, YT), pp. 1940–1943.
ICPRICPR-2012-WangGL #detection #image
A new depth descriptor for pedestrian detection in RGB-D images (NW, XG, JL), pp. 3688–3691.
ICPRICPR-2012-WangPLQHJ #detection
Color Maximal-Dissimilarity Pattern for pedestrian detection (QW, JP, GL, LQ, QH, SJ), pp. 1952–1955.
HCIDUXU-v2-2011-ArdavanC #3d #exclamation #safety #towards
Listen! Somebody Is Walking towards Your Car (Introducing the Awareness-3D Sound System into the Driver to Increase the Pedestrian’s Safety) (MA, FC), pp. 89–98.
CHICHI-2010-WilliamsonRSMJB #privacy #social
Social gravity: a virtual elastic tether for casual, privacy-preserving pedestrian rendezvous (JW, SR, CDS, RMS, MJ, SAB), pp. 1485–1494.
ICPRICPR-2010-HongCCG #detection #set
Boosted Sigma Set for Pedestrian Detection (XH, HC, XC, WG), pp. 3017–3020.
ICPRICPR-2010-KamedaO #image #navigation #retrieval
Image Retrieval of First-Person Vision for Pedestrian Navigation in Urban Area (YK, YO), pp. 364–367.
ICPRICPR-2010-MaHHL #detection
Context Inspired Pedestrian Detection in Far-Field Videos (WM, PH, LH, CL), pp. 3009–3012.
ICPRICPR-2010-RicciTZ #kernel #learning
Learning Pedestrian Trajectories with Kernels (ER, FT, GZ), pp. 149–152.
ICPRICPR-2010-ShahrokniGF #novel #performance #recognition
A Novel Shape Feature for Fast Region-Based Pedestrian Recognition (AS, DG, JMF), pp. 444–447.
ICPRICPR-2010-SzczotDL #estimation #recognition
Incorporating Lane Estimation as Context Source in Pedestrian Recognition Task (MS, ID, OL), pp. 2628–2631.
ICPRICPR-2010-TosatoFCM #detection
A Re-evaluation of Pedestrian Detection on Riemannian Manifolds (DT, MF, MC, VM), pp. 3308–3311.
ICPRICPR-2010-WidhalmB #learning
Learning Major Pedestrian Flows in Crowded Scenes (PW, NB), pp. 4064–4067.
CHICHI-2009-RukzioMH #design #evaluation #implementation #navigation #novel
Design, implementation and evaluation of a novel public display for pedestrian navigation: the rotating compass (ER, MM, RH), pp. 113–122.
SACSAC-2009-EstevesRFO #concept #framework #implementation #simulation
Conceptualization and implementation of a microscopic pedestrian simulation platform (EFE, RJFR, PAFF, ECO), pp. 2105–2106.
ICPRICPR-2008-Junejo
Camera calibration for uneven terrains by observing pedestrians (INJ), pp. 1–4.
CHICHI-2007-SeagerF #automation #navigation #physics
Comparing physical, automatic and manual map rotation for pedestrian navigation (WS, DSF), pp. 767–776.
HCIHCI-IPT-2007-BeehareeS
Minimising Pedestrian Navigational Ambiguities Through Geoannotation and Temporal Tagging (AKB, AS), pp. 748–757.
ICPRICPR-v4-2006-AlbuLCOHZPBMDDMJTGL #monitoring #named #network
MONNET: Monitoring Pedestrians with a Network of Loosely-Coupled Cameras (ABA, DL, SC, DO, PH, AZ, MP, RB, XM, RD, SD, NMB, FJ, HT, LG, FL), pp. 924–928.
ICPRICPR-v4-2006-YangLPZZ #detection #learning
Active Learning Based Pedestrian Detection in Real Scenes (TY, JL, QP, CZ, YZ), pp. 904–907.
ICEISICEIS-v5-2004-GuilletRP #adaptation
User Adaptation in a Pedestrian Guidance System for the Blind (VG, BR, JMP), pp. 69–74.
ICPRICPR-v4-2004-YangL #detection #multi
Multiple Pedestrian Detection and Tracking based on Weighted Temporal Texture Features (HDY, SWL), pp. 248–251.
ICPRICPR-v2-2000-WohlerKA #classification #image #recognition #sequence
Pedestrian Recognition by Classification of Image Sequences — Global Approaches vs. Local Spatio-Temporal Processing (CW, UK, JKA), pp. 2540–2544.
ICPRICPR-1998-HeiseleW #recognition
Motion-based recognition of pedestrians (BH, CW), pp. 1325–1330.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.