Automatic Hardware Implementation Tool for a Discrete Adaboost-Based Decision Algorithm

Mitéran, Johel; Matas, J.; Bourennane, El-Bay; Paindavoine, Michel; Dubois, Julien

doi:10.1155/asp.2005.1035

Cited by 16 publications

(11 citation statements)

References 29 publications

(26 reference statements)

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“…These operators, which represent one of the main part of the processing, can be eventually implemented in parallel [25] as discussed in Sect. 4.2.3.1.…”

Section: Supervised Classificationmentioning

confidence: 99%

“…Therefore, we have selected this algorithm despite its relatively low-processing time compared to the global system processing time. Due to its popularity in image analysis, an efficient implementation of this classifier represents a significant contribution by itself as attested to by the number of references dealing with this issue [25,39,40]. A large list of publications dealing with boosting is available on [4].…”

Section: 222mentioning

confidence: 99%

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Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

Senouci

Charfi

Heyrman

et al. 2014

J Real-Time Image Proc

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Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of a fall detection system based on such a smart camera, which allows to reduce the development time compared to standard approaches. Founded on a supervised classification approach, we propose a HW/SW implementation to detect falls in a home environment using a single camera and an optimized descriptor adapted to real-time tasks. This heterogeneous implementation is based on Xilinx's system-on-chip named Zynq. The main contributions of this work are (i) the proposal of a codesign methodology. These methodologies enable the HW/ SW partitioning to be delayed using high-level algorithmic description and high-level synthesis tools. Our approach enables fast prototyping which allows fast architecture exploration and optimisation to be performed, (ii) the design of a hardware accelerator dedicated to boostingbased classification, which is a very popular and efficient algorithm used in image analysis, (iii) the proposal of falldetection embedded in a smart camera and enabling integration into the elderly people environment. Performances of our system are finally compared to the state-of-the-art.

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“…These operators, which represent one of the main part of the processing, can be eventually implemented in parallel [25] as discussed in Sect. 4.2.3.1.…”

Section: Supervised Classificationmentioning

confidence: 99%

Section: 222mentioning

confidence: 99%

Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

Senouci

Charfi

Heyrman

et al. 2014

J Real-Time Image Proc

View full text Add to dashboard Cite

show abstract

“…The core of the training of the second stage is the hyperrectangle set S H determination from a set of samples S. We use the method proposed in [30] to train the weak classifier. The basic idea is to build around each sample {x i , y i } ∈ S a box or hyper-rectangle H(x i ) containing no sample of opposite classes, where x i is the confidence vectors of all samples in this paper and y i = ±1.…”

Section: The Second Stage Of Weak Classifiermentioning

confidence: 99%

A Reconfigurable Architecture for Rotation Invariant Multi-View Face Detection Based on a Novel Two-Stage Boosting Method

Dou

Pang

2009

EURASIP J. Adv. Signal Process.

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We present a reconfigurable architecture model for rotation invariant multi-view face detection based on a novel two-stage boosting method. A tree-structured detector hierarchy is designed to organize multiple detector nodes identifying pose ranges of faces. We propose a boosting algorithm for training the detector nodes. The strong classifier in each detector node is composed of multiple novelly designed two-stage weak classifiers. With a shared output space of multicomponents vector, each detector node deals with the multidimensional binary classification problems. The design of the hardware architecture which fully exploits the spatial and temporal parallelism is introduced in detail. We also study the reconfiguration of the architecture for finding an appropriate tradeoff among the hardware implementation cost, the detection accuracy, and speed. Experiments on FPGA show that high accuracy and marvelous speed are achieved compared with previous related works. The execution time speedups range from 14.68 to 20.86 for images with size of 160 × 120 up to 800 × 600 when our FPGA design (98 MHz) is compared with software solution on PC (Pentium 4 2.8 GHz).

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“…This is why we privilege the simple methods based on the distances between groups and the methods of the regression type. Some previous work show the feasibility of pattern recognition in FPGA based systems (Miteran J., 2005). An LDA method has been chosen.…”

Section: Pattern Recognition: Linear Discriminant Analysismentioning

confidence: 99%

DEVELOPMENT OF AN AUTOMATED DEVICE FOR SORTING SEEDS - Application on Sunflower Seeds

Muracciole¹,

Poulichet²,

Bertrand³

et al. 2007

Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics

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Purity analysis and determination of other seeds by number are still made manually. It is a repetitive task based upon visual analysis. Our work objective is to create and use a simple and quick automated system to do this task. A first step of this machine has been reached by validating the image acquisition and feeding process. The principle of this machine is based on a seeds fall with stroboscopic effect image acquisition. This article presents the first step of creating a dedicated and autonomous machine which combines embedded constraints and real time processes.

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Automatic Hardware Implementation Tool for a Discrete Adaboost-Based Decision Algorithm

Cited by 16 publications

References 29 publications

Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

A Reconfigurable Architecture for Rotation Invariant Multi-View Face Detection Based on a Novel Two-Stage Boosting Method

DEVELOPMENT OF AN AUTOMATED DEVICE FOR SORTING SEEDS - Application on Sunflower Seeds

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