project report
Pedestrian Detection/ Recognition in Computer Vision
0.1.
A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling
0.2.
filtered_channel_features_for_pedestrian_detection.md
0.3.
fine-grained_classification_of_pedestrians_in_vide.md
0.4.
learning_complexity-aware_cascades_for_deep_pedest.md
0.5.
learning_scene-specific_pedestrian_detectors_witho.md
0.6.
multispectral_pedestrian_detection_benchmark_datas.md
0.7.
pedestrian_detection_aided_by_deep_learning_semant.md
0.8.
taking_a_deeper_look_at_pedestrians.md
0.9.
understanding_pedestrian_behaviors_from_stationary.md
0.10.
Deep Learning Strong Parts for Pedestrian Detection
0.11.
Pedestrian Detection for Driving Assistance Systems: Single-frame Classification and System Level Performance
0.12.
Pyramidal Channel Features for Pedestrian Detector
0.13.
Results from a Real-time Stereo-based Pedestrian Detection System on a Moving Vehicle
0.14.
Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning
1.
pedestrian detection (system)
1.1.
Detection of Sudden Pedestrian Crossings for Driving Assistance Systems
1.2.
real-time_pedestrian_detection_in_urban_scenarios.md
1.3.
Gradient-based region of interest selection for faster pedestrian detection
2.
Mobile Detection/ Recognition
2.1.
Mobile Object Detection through Client-Server based Vote Transfer
2.2.
Recognition of Traffic Lights in Live Video Streams on Mobile Devices
2.3.
Real-Time Walk Light Detection with a Mobile Phone
2.4.
WalkSafe: A Pedestrian Safety App for Mobile Phone Users Who Walk and Talk While Crossing Roads
2.5.
A Pedestrian Passage Detection Method by Using Spinning Magnets on Corridors
2.6.
Nericell: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones
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project report
pedestrian detection (system)