Wind dynamic range video camera

A television camera apparatus is disclosed in which bright objects are attenuated to fit within the dynamic range of the system, while dim objects are not. The apparatus receives linearly polarized light from an object scene, the light being passed by a beam splitter and focused on the output plane of a liquid crystal light valve. The light valve is oriented such that, with no excitation from the cathode ray tube, all light is rotated 90 deg and focused on the input plane of the video sensor. The light is then converted to an electrical signal, which is amplified and used to excite the CRT. The resulting image is collected and focused by a lens onto the light valve which rotates the polarization vector of the light to an extent proportional to the light intensity from the CRT. The overall effect is to selectively attenuate the image pattern focused on the sensor

Multiple range imaging camera operation with minimal performance impact

Time-of-flight range imaging cameras operate by illuminating a scene with amplitude modulated light and measuring the phase shift of the modulation envelope between the emitted and reflected light. Object distance can then be calculated from this phase measurement. This approach does not work in multiple camera environments as the measured phase is corrupted by the illumination from other cameras. To minimize inaccuracies in multiple camera environments, replacing the traditional cyclic modulation with pseudo-noise amplitude modulation has been previously demonstrated. However, this technique effectively reduced the modulation frequency, therefore decreasing the distance measurement precision (which has a proportional relationship with the modulation frequency). A new modulation scheme using maximum length pseudo-random sequences binary phase encoded onto the existing cyclic amplitude modulation, is presented. The effective modulation frequency therefore remains unchanged, providing range measurements with high precision. The effectiveness of the new modulation scheme was verified using a custom time-of-flight camera based on the PMD19-K2 range imaging sensor. The new pseudo-noise modulation has no significant performance decrease in a single camera environment. In a two camera environment, the precision is only reduced by the increased photon shot noise from the second illumination source

Low-cost interactive active monocular range finder

This paper describes a low-cost interactive active monocular range finder and illustrates the effect of introducing interactivity to the range acquisition process. The range finder consists of only one camera and a laser pointer, to which three LEDs are attached. When a user scans the laser along surfaces of objects, the camera captures the image of spots (one from the laser, and the others from LEDs), and triangulation is carried out using the camera\u27s viewing direction and the optical axis of the laser. The user interaction allows the range finder to acquire range data in which the sampling rate varies across the object depending on the underlying surface structures. Moreover, the processes of separating objects from the background and/or finding parts in the object can be achieved using the operator\u27s knowledge of the objects

Video-rate or high-precision: A flexible range imaging camera

A range imaging camera produces an output similar to a digital photograph, but every pixel in the image contains distance information as well as intensity. This is useful for measuring the shape, size and location of objects in a scene, hence is well suited to certain machine vision applications. Previously we demonstrated a heterodyne range imaging system operating in a relatively high resolution (512-by-512) pixels and high precision (0.4 mm best case) configuration, but with a slow measurement rate (one every 10 s). Although this high precision range imaging is useful for some applications, the low acquisition speed is limiting in many situations. The system’s frame rate and length of acquisition is fully configurable in software, which means the measurement rate can be increased by compromising precision and image resolution. In this paper we demonstrate the flexibility of our range imaging system by showing examples of high precision ranging at slow acquisition speeds and video-rate ranging with reduced ranging precision and image resolution. We also show that the heterodyne approach and the use of more than four samples per beat cycle provides better linearity than the traditional homodyne quadrature detection approach. Finally, we comment on practical issues of frame rate and beat signal frequency selection

Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species

3D modelling by low-cost range camera: software evaluation and comparison

The aim of this work is to present a comparison among three software applications currently available for the Occipital Structure SensorTM; all these software were developed for collecting 3D models of objects easily and in real-time with this structured light range camera. The SKANECT, itSeez3D and Scanner applications were thus tested: a DUPLOTM bricks construction was scanned with the three applications and the obtained models were compared to the model virtually generated with a standard CAD software, which served as reference. The results demonstrate that all the software applications are generally characterized by the same level of geometric accuracy, which amounts to very few millimetres. However, the itSeez3D software, which requires a payment of $7 to export each model, represents surely the best solution, both from the point of view of the geometric accuracy and, mostly, at the level of the color restitution. On the other hand, Scanner, which is a free software, presents an accuracy comparable to that of itSeez3D. At the same time, though, the colors are often smoothed and not perfectly overlapped to the corresponding part of the model. Lastly, SKANECT is the software that generates the highest number of points, but it has also some issues with the rendering of the colors

Mobile Robot Range Sensing through Visual Looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer I mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.Defense Advanced Research Projects Agency; Office of Naval Research; Navy Research Laboratory (00014-96-1-0772, 00014-95-1-0409