![]() ![]() Written ASL digit for "EASY" contributed by Adrean Clark in the ASLwrite community, 2018. :)Ĭontrary to the assumption, signed languages are not easier to learn than spoken languages. It's still difficult to interpret for a native-level, fast-talking, culturally Deaf who was born into and grew up in a Deaf family, Deaf community, and Deaf schools which is a minority of a minority. This fluent level is about halfway away from the native level. Then after that, you sweat all the way to the interpreting level after several years. ![]() Hey, where are you going? Learning grammar is inevitable. Sure, for the first few signs or several signs (no different for any spoken languages) up to the beginner level. Īgain and again, a hearing person thinks that learning a signed language is easy. Image with permission from Matt and Kay Daigle. How is it easy to learn sign language? See the comics below for a short answer or the article for a long version. Synonyms: easy as pie/peasy, EFFORTLESS, FACILE, PAINLESS, SIMPLE, STRAIGHTFORWARD, SMOOTH, UNCOMPLICATED, no sweat, USER-FRIENDLY. Pronunciation (sign description): Dominant bent-flat hand (handshape), half behind non-dominant bent-flat hand (location), palms facing in (orientation), tips of dominant hand flicks twice on back of fingers of non-dominant hand.ĭeaf signers do inflect this base of word to convey synonyms such as "too easy", "easy!", "so easy", and so on. What is the sign for 'easy' in American Sign Language?ĭefinition: Achieved without great effort presenting few difficulties. How easy is it to learn sign language? Answer soon. matchShapes accepts arrays of Points as parameters, but the contours are arrays of arrays of Points.The words for 'easy' in most spoken languages and signed languages are kind of easy like "easy" in English, "facile" in French, "einfach" in German, "lehko" in Ukrainian, "laykht" in Yiddish, and and this one in ASL. These hand 'contours' are actually made of multiple contours themselves and that image that I showed earlier is actually made of these multiple contours but overlapped with eachother. The problem with it is the definition of a contour. ![]() NamedWindow( "maxim", CV_WINDOW_AUTOSIZE ) Largest_contour_index=i //Store the index of largest contourĬout<<"zaindex "<<largest_contour_index<<endl ĭrawContours( drawing, hull, largest_contour_index, color, 2, 8, hierarchy, 0, Point() ) NamedWindow( source_window, CV_WINDOW_AUTOSIZE ) ĬreateTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback ) Ĭanny( src_gray, canny_output, thresh, thresh*2, 3 ) įindContours( canny_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) ) / Load source image and convert it to gray Here's my code below(it's a bit messy as I'm testing currently). ![]() Ok, I've been playing a bit with matchShapes as berak told me. Or is there another way to match shapes? That could solve my problem, but I couldn't find any example that does for custom shapes, only for ones like rectangles, circles and triangles. Would a Haar cascade classifier work? Or would it detect two hands in different positions as hands as well? How to compare them, though? FLANN doesn't seem to work. Check O, for instance, it has no open fingers, so I thought that trying to compare contours would be the best. I was thinking that detecting by convexity hull won't work, because most of the signs are closed fists. I want my final result to be like here, so how can I compare image shapes? Is my approach wrong? For instance, check this image, it should point only to V, but it detects features in W and R, too. The problem is that this will match it with all the hands, since.well it detects them as hands. I tried comparing them using the algorithm described here, which detects similar features images have. I can get the curent hand shape using the algorithm described here, so the problem is how do I compare this shape to my database of shapes? I already detect hands, but the problem is detecting the hand shape. I want to detect ASL hand signs.įor detecting hands, I can use either detection by skin color or a haar classifier. I am a bit new to opencv and could use some help. ![]()
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