Siemens Aktiengesellschaft

Siemens Corporation

Siemens Corporate Research, Inc.

Continental Automotive Gmbh

Siemens Vdo Automotive Ag

Vdo Automotive Ag

Siemesn Corporate Research, Inc.

Continental Reifen Deutschland Gmbh

Thorsten Köhler

Ying Zhu

Ludwig Ertl

Martin Pellkofer

Dorin Comaniciu

Dirk Zittlau

Gregory Baratoff

Visvanathan Ramesh

Ulrich Wagner

Claus Bahlmann

Binglong Xie

Maneesh Kumar Singh

Henryk Frenzel

Horst Belau

Kazunori Okada

Benedicte Bascle

Stephan Voltz

Reinhard Rösl

Jörg Lehmann

Markus Christl

Andre Rieder

Karl-Heinz Eglseder

A monitoring unit for the exterior in the direction of travel of a motor vehicle includes at least one camera system with an image recording sensor. The sensor has color encoding in some regions and, otherwise, monochrome encoding. An assist system is also provided with such a monitoring unit, in particular a traffic sign and/or lane recognition assist system.

Monitoring unit and assistance system for motor vehicles

A method for vehicle detection and tracking includes acquiring video data including a plurality of frames, comparing a first frame of the acquired video data against a set of one or more vehicle detectors to form vehicle hypotheses, pruning and verifying the vehicle hypotheses using a set of course-to-fine constraints to detect a vehicle, and tracking the detected vehicle within one or more subsequent frames of the acquired video data by fusing shape template matching with one or more vehicle detectors.

System and method for vehicle detection and tracking

A method for training a system for detecting multi-class objects in an image or a video sequence is described. A common ensemble of weak classifiers for a set of object classes is identified. For each object class, a separate weighting scheme is adapted for the ensemble of weak classifiers. A method for detecting objects of multiple classes in an image or a video sequence is also disclosed. Each class is assigned a detector that is implemented by a weighted combination of weak classifiers such that all of the detectors are based on a common ensemble of weak classifiers. Then weights are individually set for each class.

Method for combining boosted classifiers for efficient multi-class object detection

A system and method for detecting and tracking an object is disclosed. A camera captures a video sequence comprised of a plurality of image frames. A processor receives the video sequence and analyzes each image frame to determine if an object is detected. The processor applies one or more classifiers to an object in each image frame and computes a confidence score based on the application of the one or more classifiers to the object. A database stores the one or more classifiers and vehicle training samples. A display displays the video sequence.

An assistance system for motor vehicles has at least one monitoring unit monitoring a space external to a vehicle, in particular in a direction of travel of the motor vehicle, with a warning zone being defined in the monitored external space on each side of a lane. The warning zone is delimited by an earliest warning line and a latest warning line encompassing the respective lane marking or, as the case may be, boundary. An evaluation unit receives the data transmitted by the monitoring unit and generates a warning signal for an acoustic, visual and/or haptic warning and/or a steering intervention if the evaluation unit detects that a defined warning threshold lying within the warning zone is exceeded. The warning signal is issued only as a function of further planned driver-adaptive conditions.

Assistance system for motor vehicles

The present invention is directed to a system and method for on-road vehicle detection. A video sequence is received that is comprised of a plurality of image frames. A potential vehicle appearance is identified in an image frame. Known vehicle appearance information and scene geometry information are used to formulate initial hypotheses about vehicle appearance. The potential vehicle appearance is tracked over multiple successive image frames. Potential motion trajectories for the potential vehicle appearance are identified over the multiple image frames. Knowledge fusion of appearance, scene geometry and motion information models are applied to each image frame containing the trajectories. A confidence score is calculated for each trajectory. A trajectory with a high confidence score is determined to represent a vehicle appearance.

System and method for on-road detection of a vehicle using knowledge fusion

A method of detecting a feature of a vehicle in an image of a vehicle includes providing a digitized image of a vehicle, providing a first filter mask over a first subdomain of the image, where the filter mask is placed to detect a feature in the image, calculating a function of a gradient of the image inside the first masked subdomain, and detecting the presence or absence of a vehicle feature within the first masked subdomain based on the value of the gradient function.

System and method for detecting features from images of vehicles

Methods for image processing for detecting and recognizing an image object include detecting an image object using pose-specific object detectors, and performing fusion of the outputs from the pose-specific object detectors. The image object is recognized using pose-specific object recognizers that use outputs from the pose-specific object detectors and the fused output of the pose-specific object detectors; and by performing fusion of the outputs of the pose-specific object recognizers to recognize the image object.

Systems and methods for face detection and recognition using infrared imaging

A system and method for detecting an occupant and head pose using stereo detectors is disclosed. In the training stage, pairs of images taken simultaneously from a pair of stereo cameras are received and components in each pair of images are identified. Features are associated with each component and a value is associated with each feature. Among them, a subset of features with best discriminative capabilities is selected and forms a strong classifier for a given component in a pair of images. In the detection stage, the strong classifiers are used in the incoming image pairs to detect components. Identified components are used to detect occupants and head pose of the occupants. Stereo detection is combined with stereo matching in a systematic way to improve occupant detection and localization.

System and method for detecting an occupant and head pose using stereo detectors

A method for detecting and recognizing at least one traffic sign is disclosed. A video sequence having a plurality of image frames is received. One or more filters are used to measure features in at least one image frame indicative of an object of interest. The measured features are combined and aggregated into a score indicating possible presence of an object. The scores are fused over multiple image frames for a robust detection. If a score indicates possible presence of an object in an area of the image frame, the area is aligned with a model. A determination is then made as to whether the area indicates a traffic sign. If the area indicates a traffic sign, the area is classified into a particular type of traffic sign. The present invention is also directed to training a system to detect and recognize traffic signs.

Method for traffic sign detection

The invention relates to a method for detecting the position of an object within the interior or a vehicle equipped with a door (). The inventive method is characterized by recording a sequence of images by means of a camera () and calculating the actual position of the object by electronically evaluating the images of the sequence of images, and generating a differential image by comparing an actual recorded image with a previously stored image. The position of the object is calculated on the basis of the differential image. To achieve this, the camera () records images of the door (). The images of the door () are evaluated and the open state of the door () is established on the basis of the differential image between the closed state and the opened state.

Method and device for optically detecting the open state of a vehicle door

The invention relates to a device () and method for detection of an object or a person in the interior of a motor vehicle. The device () is operated by means of an analytical unit (), such that the device (), for detecting an object or a person in the interior of a motor vehicle, comprising a image recording unit () and an analytical unit () for the image data transmitted from the image recording unit (), is operated in a first operating mode while an acceleration threshold value is not determined to be exceeded by the analytical unit () and in a second operation mode while the acceleration threshold value is determined to be exceeded by the analytical unit ().

Device and method for detection of an object or a person in the interior of a motor vehicle

In optical image processing methods for determining the occupation of a vehicle seat, it is advantageous to know the position of the vehicle seat (), even in the case when said seat is occupied. The above is achieved, whereby the side surface of the backrest (), facing the camera () is part of a boundary plane. A section (T, B), between a separating plane, cutting vertically through the vehicle seat and the boundary plane (B) is at least partly not covered by a seat occupant in the direction of the camera. By means of an image processing method the position of the seat may be determined.

Method and device for detecting an object in a vehicle in particular for occupant protection systems

A source image (S) that is distorted by camera optics is transformed into a corrected image (T) by using a tabular imaging rule. This transformation occurs directly during the reading out from the image sensor and in real-time. No, one or several target pixels in the target image (T) are assigned to each source pixel of the source image.

Method and device for correcting an image, particularly for occupant protection

A system and method for detecting a passing vehicle is disclosed. A video sequence comprising a plurality of image frames is received. Image intensity is measured and image motion is estimated in each image frame. A hypothesis model describing background dynamics is formulated. The measured image intensity and motion estimation is used to determine if the background dynamics has been violated in a given image frame. If the background dynamics has been violated, motion coherency is used to determine whether the violation of the background dynamics is caused by a passing vehicle.

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Deuerling, Germany

Thorsten Köhler