Towards Improved Observation Models for Visual Tracking: Selective Adaptation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Programmable Stream Processors
Computer
Integral Histogram: A Fast Way To Extract Histograms in Cartesian Spaces
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Architectures for efficient implementation of particle filters
Architectures for efficient implementation of particle filters
Cyclops: in situ image sensing and interpretation in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Adaptive Probabilistic Tracking Embedded in a Smart Camera
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Simultaneous Tracking and Action Recognition using the PCA-HOG Descriptor
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
An Integrated Memory Array Processor for Embedded Image Recognition Systems
IEEE Transactions on Computers
Computing stereo-vision in video real-time with low-cost SIMD-Hardware
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
IEEE Transactions on Signal Processing
Resampling algorithms and architectures for distributed particle filters
IEEE Transactions on Signal Processing
Efficient visual tracking using particle filter with incremental likelihood calculation
Information Sciences: an International Journal
Computers & Mathematics with Applications
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We present a parallel implementation of a histogram-based particle filter for object tracking on smart cameras based on SIMD processors. We specifically focus on parallel computation of the particle weights and parallel construction of the feature histograms since these are the major bottlenecks in standard implementations of histogram-based particle filters. The proposed algorithm can be applied with any histogram-based feature sets-we show in detail how the parallel particle filter can employ simple color histograms as well as more complex histograms of oriented gradients (HOG). The algorithm was successfully implemented on an SIMD processor and performs robust object tracking at up to 30 frames per second-a performance difficult to achieve even on a modern desktop computer.