Exemplar-based Linear Discriminant Analysis for Robust Object Tracking
Tracking-by-detection has become an attractive tracking technique, which treats tracking as a category detection problem. However, the task in tracking is to search for a specific object, rather than an object category as in detection. In this paper, we propose a novel tracking framework based on exemplar detector rather than category detector. The proposed tracker is an ensemble of exemplar-based linear discriminant analysis (ELDA) detectors. Each detector is quite specific and discriminative, because it is trained by a single object instance and massive negatives. To improve its adaptivity, we update both object and background models. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our tracking algorithm.
Code (0)
등록된 구현이 없습니다.
Tasks
ObjectObject TrackingSimilar Papers 제목 키워드 기반
Tensor object classification via multilinear discriminant analysis network
This paper proposes a multilinear discriminant analysis network (MLDANet) for the recognition of multidimensional objects, known as tensor objects. The MLDANet is a variation of linear discriminant analysis network (LDAN…
ClassificationDecoderGeneral ClassificationObjectRegularized Deep Linear Discriminant Analysis
As a non-linear extension of the classic Linear Discriminant Analysis(LDA), Deep Linear Discriminant Analysis(DLDA) replaces the original Categorical Cross Entropy(CCE) loss function with eigenvalue-based loss function t…
Randomized Kernel Multi-view Discriminant Analysis
In many artificial intelligence and computer vision systems, the same object can be observed at distinct viewpoints or by diverse sensors, which raises the challenges for recognizing objects from different, even heteroge…
Object RecognitionRobust Online Multi-Object Tracking based on Tracklet Confidence and Online Discriminative Appearance Learning
Online multi-object tracking aims at producing complete tracks of multiple objects using the information accumulated up to the present moment. It still remains a difficult problem in complex scenes, because of frequent o…
Multi-Object TrackingObjectObject TrackingOnline Multi-Object TrackingImplicitly Constrained Semi-Supervised Linear Discriminant Analysis
Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using…