Monocular pedestrian recognition using motion parallax

Enzweiler, Markus; Kanter, Patsy; Gavrila, Dariu M.

doi:10.1109/ivs.2008.4621169

Cited by 39 publications

(33 citation statements)

References 21 publications

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“…Nonpedestrian samples were the result of a pedestrian shape detection preprocessing step with a relaxed threshold setting, i.e., containing bias toward more difficult patterns. We further applied an incremental bootstrapping technique, e.g., [10], by collecting additional false positives of the corresponding classifiers on an independent sequence and retraining the classifiers on the increased data set. HOG features are extracted from those samples using 8 × 8 pixel cells, accumulated to 16 × 16 pixel blocks with eight gradient orientation bins.…”

Section: Methodsmentioning

confidence: 99%

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The Benefits of Dense Stereo for Pedestrian Detection

Keller

Enzweiler

Rohrbach

et al. 2011

IEEE Trans. Intell. Transport. Syst.

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Abstract-This paper presents a novel pedestrian detection system for intelligent vehicles. We propose the use of dense stereo for both the generation of regions of interest and pedestrian classification. Dense stereo allows the dynamic estimation of camera parameters and the road profile, which, in turn, provides strong scene constraints on possible pedestrian locations. For classification, we extract spatial features (gradient orientation histograms) directly from dense depth and intensity images. Both modalities are represented in terms of individual feature spaces, in which discriminative classifiers (linear support vector machines) are learned. We refrain from the construction of a joint feature space but instead employ a fusion of depth and intensity on the classifier level. Our experiments involve challenging image data captured in complex urban environments (i.e., undulating roads and speed bumps). Our results show a performance improvement by up to a factor of 7.5 at the classification level and up to a factor of 5 at the tracking level (reduction in false alarms at constant detection rates) over a system with static scene constraints and intensity-only classification.

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Section: Methodsmentioning

confidence: 99%

“…In [1], object hypotheses are obtained by using a subtractive clustering in the 3-D space in world coordinates. Motion information is utilized in [10] as a preprocessing step for ROI generation.…”

Section: Previous Workmentioning

confidence: 99%

The Benefits of Dense Stereo for Pedestrian Detection

Keller

Enzweiler

Rohrbach

et al. 2011

IEEE Trans. Intell. Transport. Syst.

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“…[5]), which are out of scope in this work, stereo vision is an effective approach for obtaining ROIs. In [20] a foreground region is obtained by clustering in the disparity space.…”

Section: Related Workmentioning

confidence: 99%

Dense Stereo-Based ROI Generation for Pedestrian Detection

Keller

Llorca

Gavrila

2009

Lecture Notes in Computer Science

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Abstract. This paper investigates the benefit of dense stereo for the ROI generation stage of a pedestrian detection system. Dense disparity maps allow an accurate estimation of the camera height, pitch angle and vertical road profile, which in turn enables a more precise specification of the areas on the ground where pedestrians are to be expected. An experimental comparison between sparse and dense stereo approaches is carried out on image data captured in complex urban environments (i.e. undulating roads, speed bumps). The ROI generation stage, based on dense stereo and specific camera and road parameter estimation, results in a detection performance improvement of factor five over the stateof-the-art based on ROI generation by sparse stereo. Interestingly, the added processing cost of computing dense disparity maps is at least partially amortized by the fewer ROIs that need to be processed at the system level.

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“…Applications of this technology can be found in medicine, robotics and in the entertainment industry for computer animation and motion capture for video games and movies. Popular examples are pedestrian detection for advanced driver assistance systems (Enzweiler et al 2008) and the navigation of tools in surgery (Broers et al 2007). Available tracking systems differ significantly in measuring accuracy, tracking frequency, measurement volume, costs and other specifications.…”

Section: Introductionmentioning

confidence: 99%

Precise Head Tracking in Hearing Applications

Helle¹,

Pilinski²,

Lühmann³

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The paper gives an overview about two research projects, both dealing with optical head tracking in hearing applications. As part of the project "Development of a real-time low-cost tracking system for medical and audiological problems (ELCoT)" a cost-effective single camera 3D tracking system has been developed which enables the detection of arm and head movements of human patients. Amongst others, the measuring system is designed for a new hearing test (based on the "Mainzer Kindertisch"), which analyzes the directional hearing capabilities of children in cooperation with the research project ERKI (Evaluation of acoustic sound source localization for children). As part of the research project framework "Hearing in everyday life (HALLO)" a stereo tracking system is being used for analyzing the head movement of human patients during complex acoustic events. Together with the consideration of biosignals like skin conductance the speech comprehension and listening effort of persons with reduced hearing ability, especially in situations with background noise, is evaluated. For both projects the system design, accuracy aspects and results of practical tests are discussed.

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Monocular pedestrian recognition using motion parallax

Cited by 39 publications

References 21 publications

The Benefits of Dense Stereo for Pedestrian Detection

The Benefits of Dense Stereo for Pedestrian Detection

Dense Stereo-Based ROI Generation for Pedestrian Detection

Precise Head Tracking in Hearing Applications

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