Discriminative Tracking Using Tensor Pooling
نویسندگان
چکیده
منابع مشابه
Video Representation Learning Using Discriminative Pooling
Popular deep models for action recognition in videos generate independent predictions for short clips, which are then pooled heuristically to assign an action label to the full video segment. As not all frames may characterize the underlying action—indeed, many are common across multiple actions—pooling schemes that impose equal importance on all frames might be unfavorable. In an attempt to ta...
متن کاملObject Tracking Using Discriminative Feature Selection
This paper presents an approach for evaluating multiple color histograms during object tracking. The method adaptively selects histograms that well distinguish foreground from background. The variance ratio is utilized to measure the separability of object and background and to extract top-ranked discriminative histograms. Experimental results demonstrate how this method adapts to changing appe...
متن کاملCompact Tensor Pooling for Visual Question Answering
Performing high level cognitive tasks requires the integration of feature maps with drastically different structure. In Visual Question Answering (VQA) image descriptors have spatial structures, while lexical inputs inherently follow a temporal sequence. The recently proposed Multimodal Compact Bilinear pooling (MCB) forms the outer products, via count-sketch approximation, of the visual and te...
متن کاملContinuous Multi-Views Tracking using Tensor Voting
This paper presents a new approach for continuous tracking of moving objects observed by multiple fixed cameras. The continuous tracking of moving objects in each view is realized using a Tensor Voting based approach. We infer objects trajectories by performing a perceptual grouping in 2D+t using Tensor Voting. Also, a multi-scale approach bridging gaps in object trajectories is presented. The ...
متن کاملContinuous Multi-View Tracking using Tensor Voting
We present a novel approach for continuous tracking of moving objects observed by multiple fixed cameras. The continuous tracking of moving objects in each view is realized using a Tensor Voting based approach. We infer objects trajectories by performing a perceptual grouping in 2D+t. Gaps are bridged using a multi-scale approach in object trajectories. The trajectories obtained from the multip...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Cybernetics
سال: 2016
ISSN: 2168-2267,2168-2275
DOI: 10.1109/tcyb.2015.2477879