Patrick Hebert

Median Filtering in Constant Time

The median filter is one of the basic building blocks in many image processing situations. However, its use has long been hampered by its algorithmic complexity O(tau) of in the kernel radius. With the trend toward larger images and proportionally larger filter kernels, the need for a more efficient median filtering algorithm becomes pressing. In this correspondence, a new, simple, yet much faster, algorithm exhibiting O(1) runtime complexity is described and analyzed. It is compared and benchmarked against previous algorithms. Extensions to higher dimensional or higher precision data and an approximation to a circular kernel are presented, as well.

A self-referenced hand-held range sensor

Due to its portability and great maneuverability, a handheld range sensor is a flexible solution or complement to efficiently digitize the 3-D shape for a wide variety of objects. This paper firstly presents a review of the existing hand-held technologies. Although the designation encompasses various system configurations, the structured light pattern, if any and sensor positioning are key elements. A trinocular configuration with two synchronized cameras and a light pattern projector is then proposed and tested experimentally. To eliminate the necessity for an external positioning device, a set of points are projected in the scene using a fixed and independent projector. The proposed configuration reveals interesting characteristics for calibration and measurement robustness.

Advanced surveillance systems: combining video and thermal imagery for pedestrian detection

In the current context of increased surveillance and security, more sophisticated surveillance systems are needed. One idea relies on the use of pairs of video (visible spectrum) and thermal infrared (IR) cameras located around premises of interest. To automate the system, a dedicated image processing approach is required, which is described in the paper. The first step in the proposed study is to collect a database of known scenarios both indoor and outdoor with a few pedestrians. These image sequences (video and TIR) are synchronized, geometrically corrected and temperature calibrated. The next step is to develop a segmentation strategy to extract the regions of interest (ROI) corresponding to pedestrians in the images. The retained strategy exploits the motion in the sequences. Next, the ROIs are grouped from image to image separately for both video and TIR sequences before a fusion algorithm proceeds to track and detect humans. This insures a more robust performance. Finally, specific criteria of size and temperature relevant to humans are introduced as well. Results are presented for a few typical situations.

Precise ellipse estimation without contour point extraction

This paper presents a simple linear operator that accurately estimates the parameters of ellipse features. Based on the dual conic model, the operator directly exploits the raw gradient information in the neighborhood of an ellipse’s boundary, thus avoiding the intermediate stage of precisely extracting individual edge points. Moreover, under the dual representation, the dual conic can easily be constrained to a dual ellipse when minimizing the algebraic distance. The new operator is compared to other estimation approaches, including those limited to the center position, in simulation as well as in real situation experiments.

Probabilistic octree modeling of a 3D dynamic environment

Probabilistic occupancy grids have proved to be very useful for workspace modeling in 2D environments. Due to the expansion of computational load, this approach was not tractable for mapping a 3D environment in real applications. In this paper, the original occupancy grid scheme is revisited and a generic closed-form function is introduced to avoid numerical computation of probabilities for a range sensor with Gaussian error distribution. Occupancy probabilities are computed and stored in a multiresolution octree for improved performance and compactness. Occupancy models are built in local reference frames and linked to a global reference frame through uncertain spatial relationships that can be updated dynamically. This scheme is used for building a 3D map in a telerobotic maintenance application of electric power lines where perturbations may cause motion of object assembly.

Handling Occlusions in Real-time Augmented Reality : Dealing with Movable Real and Virtual Objects

Realistic rendering in real-time augmented reality applications leads one to consider physical interactions between real and virtual worlds. One of these interactions is mutual occlusions in the rendered viewpoint. This paper presents two approaches for handling occlusions when the real objects can be displaced or deformed. The first approach is model-based. It is suited for a static viewpoint and relies only on a tracked bounding volume model within which the object’s silhouette is carved. The second approach is depthbased and makes it possible to change the viewpoint by exploiting a handheld stereo camera. Both approaches are devised to minimize the effect of real object tracking errors in the rendered viewpoint.

A Simple Operator for Very Precise Estimation of Ellipses

This paper presents a simple linear operator that accurately estimates the position and parameters of ellipse features. Based on the dual conic model, the operator avoids the intermediate stage of precisely extracting individual edge points by exploiting directly the raw gradient information in the neighborhood of an ellipses boundary. Moreover, under the dual representation, the dual conic can easily be constrained to a dual ellipse when minimizing the algebraic distance. The new operator is assessed and compared to other estimation approaches in simulation as well as in real situation experiments and shows better accuracy than the best approaches, including those limited to the center position.

Efficient camera motion and 3D recovery using an inertial sensor

This paper presents a system for 3D reconstruction using a camera combined with an inertial sensor. The system mainly exploits the orientation obtained from the inertial sensor in order to accelerate and improve the matching process between wide baseline images. The orientation further contributes to incremental 3D reconstruction of a set of feature points from linear equation systems. The processing can be performed online while using consecutive groups of three images overlapping each other. Classic or incremental bundle adjustment is applied to improve the quality of the model. Test validation has been performed on object and camera centric sequences.

Scene reconstruction and description: geometric primitive extraction from multiple viewed scattered data

Robust extraction of surface parameters from multiple view scattered and noisy 3-D measurements is a delicate task. It is shown that a stable local surface description can be extracted on sections where measurement constraints are redundant with respect to a polynomial model. A segmentation approach is developed to identify these sections. The approach is based on a measurement error model which takes into account the sensors viewpoint. An application of the approach to the extraction of straight line sections from single scan 3-D surface profiles is presented.<<ETX>>

A volumetric approach for interactive 3D modeling

Range image registration and surface reconstruction have been traditionally considered as two independent processes where the latter relies on the results of the former. This paper presents a new approach to surface recovery from range images where the two processes are unified and performed in a common volumetric representation. While the reconstructed surface is described in its implicit form as a signed distance field within a volume, registration information for matching partial surfaces is encoded in the same volume as the gradient of the distance field. This allows coupling of both reconstruction and registration and leads to an algorithm whose complexity is linear with respect to the number of images and the number of measured 3D points. The close integration and performance gain improve interactivity in the process of modeling from range image acquisition to surface reconstruction. The distances computed in the direction of filtered normals improve robustness while preserving the sharp details of the initial range images. It is shown that the integrated algorithm is tolerant to initial registration errors as well as to measurement errors. The paper describes the representation and formalizes the approach. Experimental results demonstrate performance advantages and tolerance to aforementioned types of errors.