Multiple Objects Tracking Circuit using Particle Filters with Multiple Features

Cho, Jung Uk; Jin, Seung Hun; Pham, Xuan Dai; Jeon, Jae Wook

doi:10.1109/robot.2007.364194

Cited by 15 publications

(7 citation statements)

References 17 publications

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“…Pixel intensity is also the employed visual feature in the complete HW implementation of the particle filter presented in [14–16]. Abd El‐Halym et al [14] presented three particle filter architectures: two‐step architecture where the sample, weight and output steps are carried in parallel followed by a sequential resampling step.…”

Section: Review Of the Hardware Implementations Of The Tracking Sysmentioning

confidence: 99%

See 1 more Smart Citation

Survey on hardware implementations of visual object trackers

El-Shafie

Habib

2019

IET Image Processing

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Section: Review Of the Hardware Implementations Of The Tracking Sysmentioning

confidence: 99%

“…The execution time of the algorithm is improved accordingly. The last category is to implement the tracking algorithms completely in HW [13–16]. The complete HW approach achieves significant power and speed advantage over the other categories.…”

Section: Introductionmentioning

confidence: 99%

Survey on hardware implementations of visual object trackers

El-Shafie

Habib

2019

IET Image Processing

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“…In a particle filter, several features such as image contrast, image frame difference, edge-detected silhouette, 2D or 3D contours, gray level, and RGB or HSV color spaces are used for the tracking process. The features for tracking are selected in relation to the type of moving target and the conditions of the tracking environment [25]. Color is one of the most commonly used features for it is effective in terms of scaling variation and rotation, as well as being robust to object deformations and partial occlusions within the tracking environment.…”

Section: Conventional Particle Filteringmentioning

confidence: 99%

Direction-Based Modified Particle Filter for Vehicle Tracking

Yıldırım¹,

Ince²,

Salman³

et al. 2016

ETRI J

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This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.

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“…Cho et al [16] designed the circuit to implement the algorithm using VHDL (VHSIC Hardware Description Language) in an FPGA (Field Programmable Gate Array). All the functions of the particle filter tracking system are implemented in an FPGA, and real time objects tracking has been with good performance.…”

Section: Related Workmentioning

confidence: 99%