Niko's Project Corner

Single channel speech / music separation

Hu­mans are nat­urally ca­pa­ble of sep­arat­ing an ob­ject from the back­ground of an im­age, or speech from mu­sic on an au­dio clip. Photo edit­ing is an easy task, but per­son­ally I don't know how to re­move mu­sic from the back­ground. A first ap­proach would be to use band-pass fil­ters, but it wouldn't re­sult in a sat­is­fac­tory end re­sult since there is so much over­lap be­tween the fre­quen­cies. This ar­ti­cle de­scripbes a su­per­vised learn­ing ap­proach on solv­ing this prob­lem.

Automatic map stitching

Nowa­days there are many HTML5-based map ser­vices, but typ­ically they don't of­fer any ex­port func­tion­al­ity. To cre­ate a full view of the de­sired re­gion, one can ei­ther zoom out (and lose map de­tails) or take many screen­shots of dif­fer­ent lo­ca­tions and man­ually stitch them to­gether. This pro­ject can au­to­mat­ically load all stored screen­shots, de­tect the map, crop rel­evant re­gions, de­ter­mine im­ages rel­ative off­sets and gen­er­ate the high-res out­put with zero con­fig­ura­tion from any map ser­vice.

Real-time car tracking and counting

From my of­fice win­dow I've got an un­blocked size-view to the Ring Road I (Kehä I) in Es­poo, Fin­land. It is one of the bus­iest roads in Fin­land, hav­ing up-to 100.000 cars / day. I wanted to cre­ate a pro­gram which would re­ceive a video feed from a we­bcam and would pro­cess im­ages in real time on com­mon hard­ware.

Real-time interest point tracking

As men­tioned in an other ar­ti­cle about om­ni­di­rec­tional cam­eras, my Mas­ter's The­sis' main topic was real-time in­ter­est point ex­trac­tion and track­ing on an om­ni­di­rec­tional im­age in a chal­leng­ing forest en­vi­ron­ment. I found OpenCV's rou­ti­nes mostly rather slow and run­ning in a sin­gle thread, so I ended up im­ple­ment­ing ev­ery­thing my­self to gain more con­trol on the data flow and threads' de­pen­den­cies. The im­ple­mented code would si­mul­ta­ne­ously use 4 threads on CPU and a few hun­dred on the GPU, ex­ecut­ing in­ter­est point ex­trac­tion and match­ing at 27 fps (37 ms/frame) for 1800 × 360 pix­els (≈0.65 Mpix) panoramic im­age.

Coin recognition algorithm

I de­vel­oped a coin recog­ni­tion sys­tem which can rec­og­nize eight dif­fer­ent groups of coins. The used set is all five coins of Sin­ga­pore, but a few cat­egories can­not be dis­tin­guished from each other with­out knowl­edge of the coin's size in re­la­tion to oth­ers.