GPU-FV: Realtime Fisher Vector and Its Applications in Video Monitoring

04/12/2016
by   Wenying Ma, et al.
0

Fisher vector has been widely used in many multimedia retrieval and visual recognition applications with good performance. However, the computation complexity prevents its usage in real-time video monitoring. In this work, we proposed and implemented GPU-FV, a fast Fisher vector extraction method with the help of modern GPUs. The challenge of implementing Fisher vector on GPUs lies in the data dependency in feature extraction and expensive memory access in Fisher vector computing. To handle these challenges, we carefully designed GPU-FV in a way that utilizes the computing power of GPU as much as possible, and applied optimizations such as loop tiling to boost the performance. GPU-FV is about 12 times faster than the CPU version, and 50% faster than a non-optimized GPU implementation. For standard video input (320*240), GPU-FV can process each frame within 34ms on a model GPU. Our experiments show that GPU-FV obtains a similar recognition accuracy as traditional FV on VOC 2007 and Caltech 256 image sets. We also applied GPU-FV for realtime video monitoring tasks and found that GPU-FV outperforms a number of previous works. Especially, when the number of training examples are small, GPU-FV outperforms the recent popular deep CNN features borrowed from ImageNet. The code can be downloaded from the following link https://bitbucket.org/mawenjing/gpu-fv.

READ FULL TEXT

page 6

page 7

research
10/04/2018

GPU based Parallel Optimization for Real Time Panoramic Video Stitching

Panoramic video is a sort of video recorded at the same point of view to...
research
12/10/2015

VRFP: On-the-fly Video Retrieval using Web Images and Fast Fisher Vector Products

VRFP is a real-time video retrieval framework based on short text input ...
research
04/24/2022

Compression-Based Optimizations for Out-of-Core GPU Stencil Computation

An out-of-core stencil computation code handles large data whose size is...
research
07/27/2023

Quantum Computer Simulations at Warp Speed: Assessing the Impact of GPU Acceleration

Quantum computer simulators are crucial for the development of quantum c...
research
05/18/2020

Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse Detection

The information technology revolution has facilitated reaching pornograp...
research
02/08/2017

Backpropagation Training for Fisher Vectors within Neural Networks

Fisher-Vectors (FV) encode higher-order statistics of a set of multiple ...
research
05/04/2021

TinyStack: A Minimal GPU Stack for Client ML

TinyStack is a novel way for deploying GPU-accelerated computation on mo...

Please sign up or login with your details

Forgot password? Click here to reset