Jay McGavren's Journal

$ itunes –find “Prefuse 73 Preparations” –print-info “%t - %n - %r stars”

1 - From the East (intro) - 0 stars
2 - Beaten Thursdays - 4 stars
3 - Aborted Hugs - 3 stars
4 - Class of 73 Bells (feat. School of Seven Bells) - 3 stars
5 - Girlfriend Boyfriend - 4 stars
6 - Smoking Red (feat. John Stanier) - 3 stars
7 - Prog Version Slowly Crushed - 4 stars
8 - Noreaster Cheer - 4 stars
9 - Let It Ring - 4 stars
10 - 17 Seconds Interlude (feat. Tobias Lilja) - 0 stars
11 - I Knew You Were Gonna Go - 4 stars
12 - Pomade Suite Version One - 4 stars
13 - Spaced + Dissonant - 5 stars
14 - Preparation (outro version) - 3 stars

Sigh… Only one 5-star (at least, based on my initial listen)… Lot better than Security Screenings, though.

Picasa Web Albums facial recognition - edge cases...

Finally! Picasa Web Albums rolled out its facial recognition feature. No equivalent for the desktop Picasa (yet), sadly.

It’s fast, and accurate. Some interesting bits:

-Most of the time, it has no trouble distinguishing between my pre-beard and post-beard face. -It thinks my wife and my-wife-with-sunglasses are two separate people. -It thinks my-wife-with-sunglasses and my-son-with-sunglasses are the same person. :) -Pictures of a rapidly-growing kid (age 3-5) seem to make it uncertain, though its “most likely” match is usually correct. -Based on only one picture of my brother at age 26, it just picked out a picture of him at age 11! (It wasn’t certain, but he was the most-likely match.) -A fake sneer or frown tripped it up (though again, the most-likely match was correct). -A subject losing (or gaining) a considerable amount of weight makes it uncertain. -The lighting on a face has to be REALLY poor to trip it up. -Most-likely match was right even on a face that was ~20% blocked. -Good guess on a face viewed through smoke (from a yellow smoke bomb). -Two different women with similar makeup, facial expression and pose were sorted next to each other. (And the second was mis-identified as the first, probably because she usually wears glasses and wasn’t in this shot.) -The best guess is usually of the same sex, but when it’s tripped up, members of the opposite sex may outrank the actual subject for second- and third-best guesses. -Subjects of the same (or similar) ethnicity tend to get grouped together. -Sticking your tongue out is a good way to trip it up. -Odd angles (like up from the floor) confuse it (badly). Profile-views aren’t as bad, though. -(Obviously) cartoon faces occasionally find their way into the list. -A short-lived goatee only throws it off once; after that the best guess is correct for further goatee pictures. -Bangs partially covering the eyes throw it off.

I know some of these are “duh” items, but this has just made me appreciate what a hard problem facial recognition is. Especially in the area of photos, where you’re dealing with changes in age, weight, hair, expression, poor lighting, sensor noise, and a host of other problems.

Now, how can I sort the photos back on my hard drive, since Google and I have done all this work?

Aquarium development with Alice...

Learned about Alice last night; it’s Carnegie-Mellon’s 3D cousin to MIT’s Scratch development environment. Alice is aimed at older students, and a bit more flexible.

I showed off the built-in library of objects to Diana, and the moment she saw the ocean-themed section, to my surprise, she all but elbowed me away from the keyboard. (She’s not a developer, but she is a fish nut.) Thirty minutes later, and with only occasional guidance from me, she had a school of fish robotically spinning, rolling, and moving about an ocean floor.

Drag-and-drop is definitely a good way for novices to get started programming. It’s all too easy for a beginner to give up when all they get is a blank screen due to a well-hidden typo. Mistake-resistant constructs you can scramble around and get instant feedback on keep a student moving forward.

Android 1.0 API impressions...

What they’re describing here might be applicable not just to mobile apps, but maybe applications in general. Could this become the basis of an OS for a set-top box, game console, or desktop?

An Activity is a unit of action a user can initiate. Though an Activity can be used as an application, it isn’t the same concept; an Activity could be accessed from the menu of another Activity, for example.

The lifecycle of an activity is:

onCreate()

onRestart()

Called here after an application is stopped, not during its initial startup.

onStart()

Activity is becoming visible to user.

onResume()

Activity can interact with user.

onPause()

System is about to switch to another activity.

onStop()

Activity is no longer visible to user. May be followed by onRestart() or onDestroy().

onDestroy()

During this method, if isFinishing() returns true, user requested finish. Otherwise, system did.

This model is cool because it requires that an app be ready to save its state for later reloading at any time. An app that follows this setup properly will be ready for the user to switch activities, to reflect changes to the global config, or for the phone’s battery to run low.

Notifications: I’m imagining this to be like Growl or Enso notifications. Hope I’m right, but I haven’t read far enough to know yet.

Background processes!!! The inability of third-party apps to do this is my number one complaint about the iPhone. I want a daemon that can initiate different processes when I walk into work, home, or school, and I think it simply isn’t possible on iPhone.

Facebook is asking me, on behalf of Diana:

Do you think undefined undefined?

…Sometimes, yes.