Low-level Pedestrian Detection by means of Visible and Far Infra-red Tetra-vision

Bertozzi, Massimo; Broggi, Alberto; Felisa, Mirko; Vezzoni, G.; Rose, Michael Del

doi:10.1109/ivs.2006.1689633

Cited by 43 publications

(52 citation statements)

References 12 publications

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“…The first curve has been obtained running the system using the matching equation (4). Using this method, correct detection percentage smoothly increases.…”

Section: Resultsmentioning

confidence: 99%

“…The algorithm has been developed as a part of a tetra-vision based pedestrian detection system [4], [6]; the whole system exploits the simultaneous use of two infrared and visible cameras stereo pairs. The main idea is to have both the advantages of far infrared and visible cameras trying at the same time to cope with the deficiencies of each system.…”

Section: The System Descriptionmentioning

confidence: 99%

“…In the method proposed in [4] an average mask model (see Fig. 4.a) was employed for performing the background subtraction.…”

Section: Detection Of Target Objectsmentioning

confidence: 99%

“…In addition, the second formula (5) is normalized between [-1, 1], allowing an easier way to compare the matching values than before applying equation (4). Since four different models are used, the classification in both cases is solved as a maximization problem.…”

Section: Pedestrian Detectionmentioning

confidence: 99%

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Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates

Bertozzi

Broggi

Gómez

et al. 2007

2007 IEEE Intelligent Vehicles Symposium

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Abstract-This article presents a validator stage for a pedestrian detection system based on the use of probabilistic models for the infrared domain. Four different models are employed in order to recognize the pose of the pedestrians; open, almost open, almost closed and fully closed legs are detected. In an attempt to overcome the drawbacks of template-matching in far infrared images, two different approaches are proposed. The algorithm has been tested on an experimental vehicle in different situations and a Receiver Operating Characteristic has been computed.

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“…The first curve has been obtained running the system using the matching equation (4). Using this method, correct detection percentage smoothly increases.…”

Section: Resultsmentioning

confidence: 99%

Section: The System Descriptionmentioning

confidence: 99%

“…In the method proposed in [4] an average mask model (see Fig. 4.a) was employed for performing the background subtraction.…”

Section: Detection Of Target Objectsmentioning

confidence: 99%

Section: Pedestrian Detectionmentioning

confidence: 99%

See 2 more Smart Citations

Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates

Bertozzi

Broggi

Gómez

et al. 2007

2007 IEEE Intelligent Vehicles Symposium

Self Cite

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show abstract

“…In recent years, night vision systems, exploiting advantages and benefits of IR cameras, have gained more and more interest, for the automatic detection of pedestrians at night ( [4], [6], [86]). Liu and Fujimura proposed a technique [54] as a complementary to previous shape-based approaches [96], [62].…”

Section: Pedestrian Detection/trackingmentioning

confidence: 99%

Structure from Infrared Stereo Images

Hajebi

Zelek

2008

2008 Canadian Conference on Computer and Robot Vision

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Registering Multimodal Imagery with Occluding Objects Using Mutual Information: Application to Stereo Tracking of Humans

Krotosky

Trivedi

Augmented Vision Perception in Infrared

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This chapter introduces and analyzes a method for registering multimodal images with occluding objects in the scene. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we use maximization of mutual information in sliding correspondence windows that inform a disparity voting algorithm to demonstrate successful registration of objects in color and thermal imagery where there is significant occlusion. Extensive testing of scenes with multiple objects at different depths and levels of occlusion shows high rates of successful registration. Ground truth experiments demonstrate the utility of disparity voting techniques for multimodal registration by yielding qualitative and quantitative results that outperform approaches that do not consider occlusions. A framework for tracking with the registered multimodal features is also presented and experimentally validated. IntroductionComputer vision applications are increasingly using multimodal imagery to obtain and process information about a scene. Specifically, the disparate yet complementary nature of visual and thermal imagery has been used in recent works to obtain additional information and robustness [1,2]. The use of both types of imagery yields information about the scene that is rich in color, depth, motion, and thermal detail. Such information can then be used to successfully detect, track, and analyze people and objects in the scene.To associate the information from each modality, corresponding data in each image must be successfully registered. In long-range surveillance applications [2], the cameras are assumed to be oriented in such a way that a global alignment R.I. Hammoud (ed.), Augmented Vision Perception in Infrared: Algorithms and 321

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Low-level Pedestrian Detection by means of Visible and Far Infra-red Tetra-vision

Cited by 43 publications

References 12 publications

Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates

Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates

Structure from Infrared Stereo Images

Registering Multimodal Imagery with Occluding Objects Using Mutual Information: Application to Stereo Tracking of Humans

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