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Basic Template matching has severe limitations around scaling, rotation, and perspective. In my experience it greatly underperforms compared to deep network ob
by dekhn 2mo ago
Basic Template matching has severe limitations around scaling, rotation, and perspective. In my experience it greatly underperforms compared to deep network object detectors. My experience- and I imagine others have different experiences- is that SIFT techniques also fail pretty badly with noisy data.
- mv4 2mo agoThat's correct, and I was specifically referring to the example chosen - where scale and perspective are known. Template rotation is relatively easy as well - but partial obstructions would pose a problem. Another application where template matching would work brilliantly? Car counting in parking lots using satellite imagery. Source: I did this [1] using OpenCV and template matching. Outperformed "Cars Overhead with Context" models. https://abcnews.com/International/satellite-data-suggests-coronavirus-hit-china-earlier-researchers/story?id=71123270 https://abcnews.com/International/satellite-data-suggests-co...