Fingertip in the Eye: A cascaded CNN pipeline for the real-time fingertip detection in egocentric videos

2015/11/07 by Xiaorui Liu, Liu, Xiaorui, Yichao Huang +5
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hand Gesture Recognition Systems #Human Pose and Action Recognition #cs.CV

paper · pdf · doi:10.48550/arxiv.1511.02282

5 pages, 8 figures

arxiv created 2015/11/07 · openalex publication_date 2015/11/07 · arxiv updated 2015/11/10 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

We introduce a new pipeline for hand localization and fingertip detection. For RGB images captured from an egocentric vision mobile camera, hand and fingertip detection remains a challenging problem due to factors like background complexity and hand shape variety. To address these issues accurately and robustly, we build a large scale dataset named Ego-Fingertip and propose a bi-level cascaded pipeline of convolutional neural networks, namely, Attention-based Hand Detector as well as Multi-point Fingertip Detector. The proposed method significantly tackles challenges and achieves satisfactorily accurate prediction and real-time performance compared to previous hand and fingertip detection methods.

Citations

• OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
• ImageNet Large Scale Visual Recognition Challenge
• Caffe: Convolutional Architecture for Fast Feature Embedding

Related

• Detecting Hands in Egocentric Videos: Towards Action Recognition
• Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information
• Egocentric Hand Detection Via Dynamic Region Growing
• Hand Segmentation and Fingertip Tracking from Depth Camera Images Using Deep Convolutional Neural Network and Multi-task SegNet
• Contextual Attention for Hand Detection in the Wild