ViSenze’s visual search tech on Rakuten Taiwan has promise, but can’t handle OOTD images

Text input search is passe. These days, it’s all about voice and image recognition, as seen in Apple and Google battle against one another.

While the two tech giants are duking it out in open warfare, a Singapore startup called ViSenze — a spin-off from an NUS research project — has entered the search arena via a backdoor. It has partnered with e-commerce players Rakuten and Clozette to deploy its technology enabling shoppers to upload an image and receive search results consisting of fashion items with matching clothing types, style, colour, and patterns.

The Fashion Finder can be used on two sites: www.oshare.com.tw, a joint venture between Rakuten and Singapore fashion community Clozette, and www.rakuten.com.tw/event/funsearch.

According to ViSenze, the technology has many other applications. Cars and consumer electronics websites could find it useful, while advertisers can use it to match a search result page with a visually-resonant ad. For example, a user searching for shades could see an ad showing sunglasses of a similar make, model, and color.

I find the technology reminiscent of Google’s very own image search feature. Another startup that is knee-deep in the image recognition space is Graymatics, which is applying the technology to advertising and filtering.

Relevancy is the name of the game. Whether or not ViSenze will succeed depends on its ability to serve up useful search results.

Measuring user intent is a tricky business however, since some shoppers may know exactly what they want while others adopt a search-and-see-what-happens approach (I suspect women may tend towards the latter).

In any case,  I decided to put the technology to the test.

The first thing I noticed is the lack of drag-and-drop functionality similar to what Google employs in image search and Gmail. At the moment, Fashion Finder only enables URL search and image upload, but these methods are cumbersome.

I then tested the search engine by using images from the Internet. Here are the results (search input has a red border):

Search #1: It’s an admittedly complicated photo, with the background and foreground in focus. But how else to test the prowess of ViSenze’s technology? Besides, users may want to upload Outfit of the Day (OOTD)-type photos, so the tech should ideally be competent enough to decode such pictures. Looking at the results, the algorithms were able to detect a bag in the photo, but the search results were rather inconsistent.