Vision-based pedestrian detection: the protector system

Gavrila, Dariu M.; Giebel, J.; Munder, S.

doi:10.1109/ivs.2004.1336348

Cited by 156 publications

(105 citation statements)

References 9 publications

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“…This paper builds on earlier work described in Gavrila et al (2004). We consider the main contributions of this paper the integration of modules in a multi-cue system for pedestrian detection and tracking (Section 3.2), and furthermore, the systematic procedure for parameter setting and system optimization (Section 4).…”

Section: Previous Workmentioning

confidence: 99%

Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle

Gavrila

Munder

2006

Int J Comput Vision

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468

328

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Abstract. This paper presents a multi-cue vision system for the real-time detection and tracking of pedestrians from a moving vehicle. The detection component involves a cascade of modules, each utilizing complementary visual criteria to successively narrow down the image search space, balancing robustness and efficiency considerations. Novel is the tight integration of the consecutive modules: (sparse) stereo-based ROI generation, shape-based detection, texture-based classification and (dense) stereo-based verification. For example, shape-based detection activates a weighted combination of texture-based classifiers, each attuned to a particular body pose.Performance of individual modules and their interaction is analyzed by means of Receiver Operator Characteristics (ROCs). A sequential optimization technique allows the successive combination of individual ROCs, providing optimized system parameter settings in a systematic fashion, avoiding ad-hoc parameter tuning. Application-dependent processing constraints can be incorporated in the optimization procedure.Results from extensive field tests in difficult urban traffic conditions suggest system performance is at the leading edge.

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Section: Previous Workmentioning

confidence: 99%

Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle

Gavrila

Munder

2006

Int J Comput Vision

Self Cite

468

328

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“…This work was later extended [2] to include the use of motion. Motion information had been used in other work as well [29], [6]. SVMs have been used with other descriptors for whole bodies [16] or body parts [19].…”

Section: Previous Workmentioning

confidence: 99%

People Detection Using Color and Depth Images

Salas

Tomasi

2011

Lecture Notes in Computer Science

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Abstract. We present a strategy that combines color and depth images to detect people in indoor environments. Similarity of image appearance and closeness in 3D position over time yield weights on the edges of a directed graph that we partition greedily into tracklets, sequences of chronologically ordered observations with high edge weights. Each tracklet is assigned the highest score that a Histograms-of-Oriented Gradients (HOG) person detector yields for observations in the tracklet. High-score tracklets are deemed to correspond to people. Our experiments show a significant improvement in both precision and recall when compared to the HOG detector alone.

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“…Some approaches aimed at pedestrian detection have used of dense 3-D information, but only as a validation method [9].…”

Section: A Related Workmentioning

confidence: 99%

“…In [15] the authors use far infrared cameras, hyper permutation networks, hierarchical contour matching and a cascaded classifier approach. In [9] a method using the "chamfer system", texture classification and stereo verification is presented. [13] describes a top down segmentation approach which aggregates evidence in several stages in order to detect pedestrians in crowded scenes using a fixed camera.…”

Section: Pedestrian Detection Using Dense Stereomentioning

confidence: 99%

Multi-feature walking pedestrians detection for driving assistance systems

Bota¹,

Nedesvchi²

2008

IET Intell. Transp. Syst.

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Abstract-This paper deals with a pedestrian pre-crash sensor based on dense stereovision and motion analysis. We aim to provide means to deploy safety measures before a crash occurs. Depending on the concrete selected actuator, it could be interesting to know the type of object (e. g. vehicle, pedestrian, bicyclist, etc.) involved in the collision. Some actuators need the information about the collision partner type, because they have to be triggered only in specific situations, or in a situation dependent manner. We present a pedestrian detection system based on dense stereo and motion, acting as pre-crash sensor. In order to detect pedestrians, we use simple features such as object size, speed, and also more complex, motion based features. All these features are combined into a flexible, Bayesian framework.

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Vision-based pedestrian detection: the protector system

Cited by 156 publications

References 9 publications

Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle

Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle

People Detection Using Color and Depth Images

Multi-feature walking pedestrians detection for driving assistance systems

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