DepthfromDefocus-文獻(xiàn)閱讀.doc

Depth from Defocus:A Spatial Domain Approach(1) Title, authors, conf./journal, page no., year.Title Depth from Defocus:A Spatial Domain ApproachAuthorsMurali Subbarao ,Gopal Sunrya DATE Junepage no.272/294year2011(2) Motivation (why the problem is important?)Motivation one: Passive techniques of ranging or determining distance of objects from a camera is an important problem in computer vision.Motivation two:STM is very fast in comparison with Depth-from-Focus methods which search for the lens position or focal length of best focus.(3) Problem (What is the exact problem they want to solve, input/output)How to determin distance of objects and rapidly autofocus of camera system only by two images taken with different camera parameters such as lens position,focal length,and aperture diameter.(4) Techniques (How they solve the problem, by what kind of techniques)To Calculate distance of object:First: capture two digital images with different camera parametersSecond:Smooth the two images partlyThird:Perform Laplacian operation on the smoothed imagesFourth:Calculate the 2Fifth:Calculate distance of object(5) Experiments(How they conduct experiments, environments, results, conclusions)STM described above was implemented on a camera system named Stonybrook Passive Autofocusing and Ranging Camera System (SPARCS).Environments:SPARCS consists of a SONY XC-711 CCD camera and an Olympus 35-70 mm motorized lens.Images from the camera are captured by a frame grabber board (Quickcapture DT2953 of Data Translation).The frame grabber board resides in an IBM PS/2 (model 70)personal computer.The captured images are processed in the PS/2 computer.Different versions:1. only the lens position was changed in obtaining two images gl and g2,but the diameter of the lens aperture was not changed.Changing the lens position changes the parameters s and f .2. only the diameter of the lens aperture was changed but the other camera parameters s,f were unchanged in obtaining the two images.Results:1.Result from version one:(6) Thoughts (How can we do something new based on this paper)For different architectures, the IO requests is different, we can extend this idea into different architectures with different access patterns.2. Result from version two:Conclusions:a new DFD method named STM is useful for passive rangingand rapid autofocusing.(6) Thoughts (How can we do something new based on this paper)The ranging accuracy of this method can be improved somewhat by using a DFF method which searches for the best focused position in a small interval near the distance estimated