Silhouette-Based View-Embeddings for Gait Recognition Under Multiple Views
Tianrui Chai, Xinyu Mei, Annan Li, Yunhong Wang
Abstract
Gait recognition under multiple views is an important computer vision and pattern recognition task. In the emerging convolutional neural network based approaches, the information of view angle is ignored to some extent. Instead of direct view estimation and training view-specific recognition models, we propose a compatible framework that can embed view information into existing architectures of gait recognition. The embedding is simply achieved by a selective projection layer. Experimental results on two large public datasets show that the proposed framework is very effective.
Topics & Concepts
SilhouetteComputer scienceConvolutional neural networkGaitTask (project management)EmbeddingArtificial intelligenceProjection (relational algebra)Pattern recognition (psychology)Artificial neural networkComputer visionMachine learningEngineeringBiologyAlgorithmPhysiologySystems engineeringGait Recognition and AnalysisIndoor and Outdoor Localization TechnologiesDiabetic Foot Ulcer Assessment and Management