Depth from triangulation has traditionally been investigated in a number of independent threads of research, with methods such as stereo, laser scanning, and coded structured light considered separately. We propose a common framework called spacetime stereo that unifies and generalizes many of these previous methods. To show the practical utility of the framework, we develop two new algorithms for depth estimation: depth from unstructured illumination change and depth estimation in dynamic scenes. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.

Spacetime stereo: a unifying framework for depth from triangulation

Depth from triangulation has traditionally been treated in a number of separate threads in the computer vision literature, with methods like stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework, spacetime stereo, which unifies many of these previous methods. Viewing specific techniques as special cases of this general framework leads to insights regarding the solutions to many of the traditional problems of individual techniques. Specifically, we discuss a number of innovative possible applications such as improved recovery of static scenes under variable illumination, spacetime stereo for moving objects, structured light and laser scanning with multiple simultaneous stripes or patterns, and laser scanning of shiny objects. To suggest the practical utility of the framework, we use it to analyze one of these applications: recovery of static scenes under variable, but uncontrolled, illumination. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.

https://graphics.stanford.edu/papers/SpacetimeStereo/Princeton-TR-689-04.pdf

In this paper, we present a brief survey of the technologies currently available for range sensing, of their use in robotics applications, and of emerging technologies for future systems. The paper is organized by type of sensing: laser range finders, triangulation range finders, and passive stereo. A separate section focuses on current development in the area of nonscanning sensors, a critical area to achieve range sensing performance comparable to that of conventional cameras. The presentation of the different technologies is based on many recent examples from robotics research.

Active and passive range sensing for robotics

The authors present experimental results from an array of cells, each of which contains a photodiode and the analog signal-processing circuitry needed for light-stripe range finding. Prototype circuits were fabricated through MOSIS in a 2- mu m CMOS p-well double-metal, double-poly process. This design builds on some of the ideas that have been developed for ICs that integrate signal-processing circuitry with photosensors. In the case of light-stripe range finding, the increase in cell complexity from sensing only to sensing and processing makes the modification of the operational principle of range finding practical, which in turn results in a dramatic improvement in performance. The IC array of photosensor and analog signal processor cells that acquires 1000 frames of light-stripe range data per second-two orders of magnitude faster than conventional light-stripe range-finding methods. The highly parallel range-finding algorithm used requires that the output of each photosensor site be continuously monitored. Prototype high-speed range-finding systems have been built using a 5*5 array and a 28*32 array of these sensing elements. >

/pdf/integrated-sensor-and-range-finding-analog-signal-processor-8rh1a5cqob.pdf

Integrated sensor and range-finding analog signal processor

The authors present a very fast lightstripe rangefinder based on an IC array of photoreceptor and analog signal processor cells which acquires 1000 frames of range image per second-two orders of magnitude faster than currently available rangefinding methods. Unlike a conventional lightstripe range-finder, which obtains a frame of range image by the step-and-repeat process of projecting a stripe and grabbing and analyzing a camera image, the VLSI sensor array of this rangefinder gathers range data in parallel as a scene is swept continuously by a moving stripe. Each cell continuously monitors the output of its photoreceptor, and detects and remembers the time at which it observed the peak incident light intensity during the sweep of the stripe. Prototype rangefinding systems have been built using a 28*32 array of these sensing elements. >

A very fast VLSI rangefinder

We present a new type of high speed range finder system that is based on the principle of triangulation range-finding. One of the unique elements of this system is a novel custom range sensor. This sensor consists of a 2D array of discrete photo-detectors. Each photo-detector is attached to an individual memory element. A slit-ray is used to illuminate the object which is then imaged by the sensor. The slit-ray is scanned at a constant angular velocity, so elapsed time is a direct function of the direction of the slit source. This elapsed time is latched into each individual memory element when the corresponding detector is triggered. The system can acquire the basic data required for range computation without repeatedly scanning the sensor many times. The slit-ray scans the entire object once at high speed. The resulting reflected energy strip sweeps across the sensor triggering the photo-detectors in succession. The expected time to acquire the data is approximately 1 millisecond for a 100x100 pixel range data. The sensor is scanned only once at the end of data acquisition for transferring the stored data to a host processing computer. The range information for each pixel is obtained from the location of the pixel and the value of time (direction of the slit source) stored in the attached memory element. We have implemented this system in an abbreviated manner to verify the method. The implementation uses a 47 x 47 array of photo-transistors. Because of the practical difficulty of hooking up the entire array to individual memories and the magnitude of the hardware involved, the implementation uses only 47 memories corresponding to a row at a time. The sensor is energized a row at a time and the laser scanned. This yields one row of data at a time as we described before. In order to obtain the whole image, we repeat this procedure as many times as we have rows, i.e, 47 times. This is not due to any inherent limitation of the method, but due to implementational difficulties in the experimental system. This can be rectified when the sensor is emitted to custom VLSI hardware. The time to completely obtain a frame of data (47 x47) is approximately 80 milliseconds. The depth measurment error is less than 1.0%.

Yukio Sato

Papers

High Speed Rangefinder